{"as_of":"2026-08-15T21:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5157f00fa53a76e8ba76bd2470f41a2fbf42d3d6d61fa0b318a036d7c7aa9dd2","coverage":[{"denominator":103,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T11:34:23.075134Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1908.09653/citation-record","integrity":"/paper/1908.09653/integrity","json":"/paper/1908.09653/citation-record.json","paper":"/paper/1908.09653"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.674254Z","title":"Integration of metabolomics and transcriptomics reveals a complex diet of mycobacterium tuberculosis during early macrophage infection,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.674254Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:ac28a5ab15bf5ccda0a7e1c6b33fd9381551df8b0e3a351de858f2599eff8b37","observation_id":"7d33faf4-d44e-4008-8fa2-c17be5436307","resolution":{"observed_at":"2026-08-14T11:34:22.674254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.680210Z","title":"A methodology for sensor fusion design: Application to fruit quality assessment,","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.680210Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:fec69dee749a9c6a9d3fe8f05292b7604d3ec524903f30f3d08a66ece38ae51e","observation_id":"bf0f32be-4e15-4173-913f-ef715ccb7f8c","resolution":{"observed_at":"2026-08-14T11:34:22.680210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.685627Z","title":"On the increase of predictive performance with high-level data fusion,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.685627Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:95c1084f03be07246ff74d250a12124dd9ff6e4b681f179df6107a990cfd4c16","observation_id":"e15de075-1369-4e17-ab2b-ad9e47b930f0","resolution":{"observed_at":"2026-08-14T11:34:22.685627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.691165Z","title":"On the theory of scales of measurement,","venue":null,"work_id":null,"year":1946},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.691165Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:faccc6c022315c76fe2d716f43c868b6578c687fd9f9e5050f55229de92f32d7","observation_id":"7cfe16dc-2092-49ab-9d05-a644885982e5","resolution":{"observed_at":"2026-08-14T11:34:22.691165Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.696153Z","title":"Basic measurement theory,","venue":null,"work_id":null,"year":1962},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.696153Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:a31f6d9951e41b2755047031972e174c64d7cf6dd6358bf3bc9382431927061e","observation_id":"17d47431-a200-4632-a516-1e659b831720","resolution":{"observed_at":"2026-08-14T11:34:22.696153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.701126Z","title":"Krantz, R","venue":null,"work_id":null,"year":1971},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.701126Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:98b7de5485508f4f5e66b1bb2abdc3368f3478c2a7cd8be0075002051163d04d","observation_id":"44880782-daca-46dc-bbba-4766c900f1d7","resolution":{"observed_at":"2026-08-14T11:34:22.701126Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.705652Z","title":"On the scales of measurement,","venue":null,"work_id":null,"year":1981},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.705652Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:de34ea0792c4a9f77043fdf37fff3ad2529227be319c9e0b4cecc87f279565d2","observation_id":"55fee992-5156-4834-9afc-1e2eaa83f2f2","resolution":{"observed_at":"2026-08-14T11:34:22.705652Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.709601Z","title":"Measurement - the theory of numerical assign- ments,","venue":null,"work_id":null,"year":1986},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.709601Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:342e4f0b5be7cf364aedea8e176d640ad6c145fe0dee1ae07caac4619a225b6a","observation_id":"3b70ed0c-a1a1-4189-8f5e-e6c5b5a1dcd4","resolution":{"observed_at":"2026-08-14T11:34:22.709601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.713679Z","title":"Measurement scales on the continuum,","venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.713679Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:f4b643f9d998c14478205828e518756cf333532efdf655486d54ba966a86f165","observation_id":"51946d4f-6b0a-420e-8c40-9d3d777852a2","resolution":{"observed_at":"2026-08-14T11:34:22.713679Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.717779Z","title":"Statistics and the theory of measurement,","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.717779Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:7252d5bb08c3061d46a531cf17d85631a7bb4e376e7eccb90687ebc898e9d05a","observation_id":"3dd604d6-7484-4d22-8c16-3aee74d76a6b","resolution":{"observed_at":"2026-08-14T11:34:22.717779Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.723114Z","title":"A theory of appropriate statistics,","venue":null,"work_id":null,"year":1965},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.723114Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:1005f701280d4c64920cff4f6144004bbc919dc78ed4681161b44990c83cf741","observation_id":"8bcfab74-8985-4191-a047-26128168bcb5","resolution":{"observed_at":"2026-08-14T11:34:22.723114Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.728297Z","title":"Measurement scales and statistics - a clash of paradigms,","venue":null,"work_id":null,"year":1986},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.728297Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:0a7e44b33816a2021e79c0f77ce620a9365c1fd858ebfb41766f76e048c5a31d","observation_id":"42cf7d1a-a393-42dc-a683-7ff78dfde0a0","resolution":{"observed_at":"2026-08-14T11:34:22.728297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.733180Z","title":"Agresti, Categorical data analysis","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.733180Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:e16f1e9d6fac90970adf2f3bd04fcacc4f3b58c308cb7504cb2f296f01eecce6","observation_id":"dfb1daae-1fcc-4d4f-8336-98354d1e04b1","resolution":{"observed_at":"2026-08-14T11:34:22.733180Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.738511Z","title":"Common and distinct components in data fusion,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.738511Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:50b8cb9b6d9898c170102860234c3a20e6a5af4d23a5fa3d73a7dbd1310c8525","observation_id":"20c26644-1fbe-49eb-9eb9-0afca6b856ff","resolution":{"observed_at":"2026-08-14T11:34:22.738511Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06573","last_updated":"2017-07-20T15:30:54Z","snapshot_observed_at":"2026-08-15T15:50:08.978105Z","submitted_at":"2017-07-20T15:30:54Z","title":"Structural Learning and Integrative Decomposition of Multi-View Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06573","snapshot_observed_at":"2026-08-14T11:34:22.743362Z","title":"Structural learning and integrative decomposition of multi-view data,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.743362Z"},"links":{"cited_paper":"/paper/1707.06573","citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:90f12386d0a1f8e725c5cdeb0a5acce4ca13fe62dc172735327925617dc25111","observation_id":"5dfd5007-8b4b-458d-a611-c941dab045f3","resolution":{"observed_at":"2026-08-14T11:34:22.743362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.748851Z","title":"Variable selection via nonconcave penalized likelihood and its oracle properties,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.748851Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:0e4ec8626b395ffd6a680146699359baea999d25637b2e1ccd78fd5230579bc7","observation_id":"f24afff2-f9d6-4448-bf2a-5ff52f20c425","resolution":{"observed_at":"2026-08-14T11:34:22.748851Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.753957Z","title":"Jolliﬀe, Principal component analysis","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.753957Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:21644e37fb1e3505c0117d82a636cde1d39f556e7bb7acefc32641a246bd84ee","observation_id":"eae112e0-faf9-4a70-a23b-a39712d42b10","resolution":{"observed_at":"2026-08-14T11:34:22.753957Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.759029Z","title":"Optimal shrinkage of singular values,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.759029Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:8d9a08e2fc2d92c5b880421d860561f44dd8d17e63db97ba4dfbad1fa298385b","observation_id":"16835b00-1e44-4b44-bbc3-bf5fbfd3842b","resolution":{"observed_at":"2026-08-14T11:34:22.759029Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.763453Z","title":"Sparse inverse covariance esti- mation with the graphical lasso,","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.763453Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:d00f9a823fc40768d6d40e8d18cac3766a8f3d333d870d439f84f7506f5b3c3b","observation_id":"813162d9-d4d9-4310-8381-29ecfd4d2c7d","resolution":{"observed_at":"2026-08-14T11:34:22.763453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.767492Z","title":"Sparsity and smoothness via the fused lasso,","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.767492Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:1b7f2dac851a9c9dc26fef4f5096743c627fa750bd3ac47415edef1b10c26586","observation_id":"b16a44d2-776e-4650-ae4a-cbb0ef0cc118","resolution":{"observed_at":"2026-08-14T11:34:22.767492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.771956Z","title":"A penalized matrix decom- position, with applications to sparse principal components and canonical correlation analysis,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.771956Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:3fb6124fe067f1d9e5f3b99cba7be6d3e58b83ee645caf514ac61361269cdd1d","observation_id":"5168d0d3-d061-489e-9077-4eeeb35aae1a","resolution":{"observed_at":"2026-08-14T11:34:22.771956Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.775940Z","title":"A selective review of group selection in high-dimensional models,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.775940Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:a89096599b7af84dfd1e7741754acb1b9670a143dc8ee4b6b2fcc120d822551f","observation_id":"ffed0b07-5c4c-4a46-b53a-91817c5fa0a1","resolution":{"observed_at":"2026-08-14T11:34:22.775940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.780039Z","title":"Regression shrinkage and selection via the lasso,","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.780039Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:8e966b151896097f0b18ce27e0e048d10772ed370bfe737e27698201de96e7b3","observation_id":"ea3dc045-0d89-4f28-98a5-7d6cdf4ab72a","resolution":{"observed_at":"2026-08-14T11:34:22.780039Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:22.783782Z","title":"Least angle regres- sion,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.783782Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:213e9021f7102c009c4a23e1a6489f1145063352ce1e648a24b4231d2df3ad82","observation_id":"7a5b35c3-13b2-4267-85c0-ca34465dc05f","resolution":{"observed_at":"2026-08-14T11:34:22.783782Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.146829Z","title":"Proximal algorithms,","venue":null,"work_id":"a5f0b634-6df5-49f9-8409-7432de3b275a","year":2014},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.787767Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:443575bef71ffae53e976fc923b4e8d1333339435c3d2c9431b51a1e94751143","observation_id":"98bec0ab-be1e-49d1-866b-f23bf60299f4","resolution":{"observed_at":"2026-08-14T11:34:24.150554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.134260Z","title":"Stability selection,","venue":null,"work_id":"4f87fd74-8335-485d-ab0b-dcd6ff8a0bad","year":2010},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.791299Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:bc7a91c2e4797e4208b94c6a417cd41f0554ea9c15752423b05a31d8e894e9da","observation_id":"0e67d111-64e5-4ac2-a260-bd96cb61f84f","resolution":{"observed_at":"2026-08-14T11:34:24.138043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.122070Z","title":"Generalized double Pareto shrink- age,","venue":null,"work_id":"7c7f69d8-087d-46e4-9853-f485b4347fcb","year":2013},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.795547Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:ad92d2202d550fffbe1ade21d7ac3c485527079d07426329da5230cd65ed79f4","observation_id":"f9a188f6-a97c-4266-b287-5b2e49fdfaa2","resolution":{"observed_at":"2026-08-14T11:34:24.125968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.109852Z","title":"Performance of meth- ods that separate common and distinct variation in multiple data blocks,","venue":null,"work_id":"e10bd9ee-9598-427e-b7b4-6d3852d705e9","year":2019},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.800402Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:49f207b482dcaa3e2115aac1ae2afa01d2aa120271728833b1329979f6001a73","observation_id":"82627f2a-a9f8-413b-b0cf-56cbc1d1f1b0","resolution":{"observed_at":"2026-08-14T11:34:24.113785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.097077Z","title":"Comprehensive genomic characterization deﬁnes human glioblastoma genes and core pathways,","venue":null,"work_id":"3f6dde19-4d51-43b4-ba78-db41e98fca91","year":2008},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.804522Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:65f25b37f51e856d138fe63c89321a6cb6e5a294c334e5ec88cb5cf19b0ea549","observation_id":"c27aa0f8-ac09-46c3-9ea0-c3e9bdabaede","resolution":{"observed_at":"2026-08-14T11:34:24.101154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.084541Z","title":"A landscape of pharmacogenomic interactions in cancer,","venue":null,"work_id":"8fc9102f-a129-48f3-8e0c-115d973d7477","year":2016},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.808264Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:c52acbe3e01a16ece1a20844dbe29ef79fadd02bde908bd37325f419ec4c9b26","observation_id":"ccedecb2-d6ef-46e3-b2ec-99609fa28246","resolution":{"observed_at":"2026-08-14T11:34:24.088582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.071310Z","title":"Detecting independent and recurrent copy number aberrations using interval graphs,","venue":null,"work_id":"be3c0b76-8332-4b0e-83d2-01f06e72fcc3","year":2014},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.811711Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:770b1e4afc0e80ff4ea9311098222a0165bf5e2edcaf1e247a41b99032fc58ff","observation_id":"82bae335-8191-4bdb-b5b6-c80e182436c3","resolution":{"observed_at":"2026-08-14T11:34:24.075774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.058202Z","title":"Quantifying qualitative data,","venue":null,"work_id":"a2274917-acff-40e8-8b93-78a892f30910","year":1980},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.815425Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:0bbbc6f312cf481d9fb4dfc69fff72080fedb2f94ad4ef199674f9242039f76e","observation_id":"5a9fb18e-e8b7-49bb-8a60-63d9a91b4e8c","resolution":{"observed_at":"2026-08-14T11:34:24.062072Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.045134Z","title":"A generalization of princi- pal component analysis to the exponential family,","venue":null,"work_id":"fd6ad21b-cb9d-4574-baac-7bd4c45a902d","year":2001},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.818960Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:17d34be90c041249c583e45ea8eb8bc9faecbb72aebb743c550d83a79b3df012","observation_id":"9f801d41-edff-4ad1-9241-3d11ee296667","resolution":{"observed_at":"2026-08-14T11:34:24.049157Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.032204Z","title":"A generalized linear model for principal component analysis of binary data.,","venue":null,"work_id":"43f76255-7022-4b9e-bca0-0ff9e3d09936","year":2003},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.822543Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:62db4683ef880385bec63409bd922c8ec546753f87cdef7e8064a8bd560ad3ae","observation_id":"70c2d6c7-ae99-46dd-b65c-1e18a147dce5","resolution":{"observed_at":"2026-08-14T11:34:24.036226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.020104Z","title":null,"venue":null,"work_id":"d1e02624-c5a9-4a4f-8a52-c28673160766","year":2015},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.826478Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:02e5c62103894b2246b998ce65c6a327c461347d9d82e511a0621e4cdb58cb38","observation_id":"181a6d6d-dfde-4613-b53c-1cc1ce156d13","resolution":{"observed_at":"2026-08-14T11:34:24.023962Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:24.007445Z","title":"Giﬁ methods for optimal scaling in R: the package homals,","venue":null,"work_id":"6ab152e4-6ab4-4896-915e-bb3feb729631","year":2009},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.830182Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:60b82da5b0a564cd11fb12bf764f7923f1fcaa42af0922e09efdac1f1f96218a","observation_id":"5f473b62-7acd-4ce4-a39e-b24634b2f427","resolution":{"observed_at":"2026-08-14T11:34:24.011336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.995230Z","title":null,"venue":null,"work_id":"76c3e156-fc63-4f50-b891-44c92310d800","year":2016},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.833988Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:8c831ebefc5b9dcb1d70a900a555f21ea3669016c6f420581d2995b4fabdf550","observation_id":"5340a438-b586-4c59-9a2e-5ae0cd22e09d","resolution":{"observed_at":"2026-08-14T11:34:23.998825Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.982901Z","title":null,"venue":null,"work_id":"45d7e0e7-5435-4552-8c42-c0f937efe5bb","year":1989},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.837731Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:a6e33dc6ffd840cbb09b36af576c92c634dfc5d0ee8373a28a0582773722a483","observation_id":"cfb11543-669a-4fac-9665-7e509032150b","resolution":{"observed_at":"2026-08-14T11:34:23.986606Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.970315Z","title":"On lines and planes of closest ﬁt to systems of points in space,","venue":null,"work_id":"13d9974e-5a8c-438e-8126-0e69a6538c9c","year":1901},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.841260Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:9e1440991c4623fde116b1bcc5fe3fae55110046d80959cf1c2e31d98f3a2036","observation_id":"d76bcde6-cd76-4c1d-9aae-3fb33dbcfb7a","resolution":{"observed_at":"2026-08-14T11:34:23.974591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.958048Z","title":"Sparse principal component anal- ysis,","venue":null,"work_id":"d42fbec9-c626-4495-8eef-be1a4acb3e2a","year":2006},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.845007Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:18fb7044fdcaa69e038aaf83dcbf71f5f08e8a7f83f14c634f8d53397f90121f","observation_id":"7cfaab11-ca9a-48e7-b15d-50dd2cb7a14c","resolution":{"observed_at":"2026-08-14T11:34:23.961850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.945504Z","title":null,"venue":null,"work_id":"4f130acc-5bb6-40f7-829f-b69ecfdd5ff2","year":1993},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.848709Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:1200e0ec016c3e466325674a947f8d8ff6bd79807f56fbcf8ac437c35cf40d41","observation_id":"742eb303-0145-40ad-9fbc-8e6ba5c66445","resolution":{"observed_at":"2026-08-14T11:34:23.949361Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.932760Z","title":"Probabilistic principal component anal- ysis,","venue":null,"work_id":"f0522e73-878a-413b-9955-db2cb2198475","year":1999},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.852269Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:6f98522e4e31992832f1805b8a5cbaa89b9b6c0e864844637f287b66117217f8","observation_id":"fbc5c04e-0cbd-4017-ba92-b65e6dba175f","resolution":{"observed_at":"2026-08-14T11:34:23.936702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.920120Z","title":"Principal component analysis of binary data by iterated singular value decomposition,","venue":null,"work_id":"69c3a13c-d038-458b-a9ad-009912f73752","year":2006},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.856064Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:77ad83ef9a7bd6918d182e029760baacfbca11be6c15eb67c08fc5605a0f67bc","observation_id":"dd47af04-189a-4b04-9d77-21d21f9fdd2e","resolution":{"observed_at":"2026-08-14T11:34:23.924061Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.907469Z","title":"Generalized low rank models,","venue":null,"work_id":"b79c0c8a-a195-48fd-bbb2-97ec1205a170","year":2016},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.860075Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:34f80ebbe44f84f2e8b564d275dafdd4386dfb8d3a6531d3f317173ad3e9340f","observation_id":"7bca1846-125d-4f1d-9c07-208c0fdbe3a1","resolution":{"observed_at":"2026-08-14T11:34:23.911409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.895167Z","title":"Giﬁ, Nonlinear multivariate analysis","venue":null,"work_id":"877855e5-e7b1-400e-acbb-60bad045d034","year":1990},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.863809Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:d7c7cbe9062937d12d07724729d4e2ec7ae087aa06e8d466e36ede012e6ccbd5","observation_id":"9109e0e8-1d54-4be1-a2b7-38c5a5a11058","resolution":{"observed_at":"2026-08-14T11:34:23.898803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.882121Z","title":"The role of balanced training and testing data sets for binary classiﬁers in bioinformatics,","venue":null,"work_id":"50c04cbb-f4fa-454b-a834-7f4f8d9afe63","year":2013},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.867595Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:ddad93ed6202ff6004d27737f579ef7b4210788c2fdcced54f8392da03abc63e","observation_id":"f626d101-624e-42df-88be-4dc7fca079d4","resolution":{"observed_at":"2026-08-14T11:34:23.886165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.869102Z","title":"Cross-validatory estimation of the number of components in factor and principal components models,","venue":null,"work_id":"fb80b2a3-3960-4119-a28a-8f7f49862136","year":1978},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.871608Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:551e163a69f8257dfdad3d44385e840f284eee8e882b6106a9b8dae72604e147","observation_id":"892a3d37-3ac5-433b-8c7d-e37cb9e4c30f","resolution":{"observed_at":"2026-08-14T11:34:23.873480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.856506Z","title":"Cross-validation of component models: A critical look at current methods,","venue":null,"work_id":"81732a03-2ac5-46e1-b35c-1dba6d127e9a","year":2008},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.875530Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:3742608b9b51628be3dbbfe0dbff3f4111d1171b36b43af1ff3e0c263cd0ebfd","observation_id":"b2760afd-5cfa-45b2-b82f-752c0f6b47e6","resolution":{"observed_at":"2026-08-14T11:34:23.860428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.844241Z","title":"R Foundation for Statistical Computing, Vienna, Austria, 2008","venue":null,"work_id":"cfd46321-0fb2-4f2a-9118-013badcfbf9d","year":2008},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.879370Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:44aca95d4491be04861b9a24d7d8ebc1aac22ae8e86e76e5ed7c24441f5c89b9","observation_id":"9c70068b-fd0f-4a60-a70b-d343fd7f1f57","resolution":{"observed_at":"2026-08-14T11:34:23.848225Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.831369Z","title":"pcaMethods–a bioconduc- tor package providing PCA methods for incomplete data,","venue":null,"work_id":"8613fdf7-7912-4021-b9ee-1c6f5e1b536b","year":2007},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.882966Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:afea7370042b846692a760d198a606ce0d5ec5a488dadae4241e7dad420731ca","observation_id":"1521e7fc-69bb-438e-9878-20bffd0896ad","resolution":{"observed_at":"2026-08-14T11:34:23.835410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1603.03174","last_updated":"2016-03-10T08:01:08Z","snapshot_observed_at":"2026-08-14T22:06:41.395266Z","submitted_at":"2016-03-10T08:01:08Z","title":"Multinomial Multiple Correspondence Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.03174","snapshot_observed_at":"2026-08-14T11:34:22.887483Z","title":"Multinomial multiple correspondence analy- sis,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.887483Z"},"links":{"cited_paper":"/paper/1603.03174","citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:be45a761fe8457d30e598764b4c6fcca2367545aca32afaecda0ed3bb9e88c06","observation_id":"3e2a90ff-4c65-4af2-ab57-651937f68fba","resolution":{"observed_at":"2026-08-14T11:34:22.887483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.818960Z","title":"1-Bit matrix completion,","venue":null,"work_id":"f5e3ce3c-e6c0-4fc6-8e6f-55958687017b","year":2014},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.891454Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:fd8204d7d8cd8ee5aa16cc3f5b231f68ec20087dd9998c51755d001b0afef6d1","observation_id":"59dfc055-2599-47bd-97ab-d5a06d2fc800","resolution":{"observed_at":"2026-08-14T11:34:23.822858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.806053Z","title":"Reconstruction of a low-rank matrix in the presence of gaussian noise,","venue":null,"work_id":"2936ba78-7b4e-4434-8be8-9769996be42b","year":2013},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.895171Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:a52f4f2f153454c73a88678cf0db270f3d730f8c26148c0a1690213bb8ab6952","observation_id":"0cd8d377-fb92-432d-9477-dce8b9dccf0f","resolution":{"observed_at":"2026-08-14T11:34:23.810078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.793428Z","title":"Adaptive shrinkage of singular values,","venue":null,"work_id":"47ede5fc-7132-4307-9892-4b55fec935a6","year":2016},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.899237Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:57d2cfd16aafbf59b1249f3d3466a17f25db2637f9eb9ea2bfbac9b3236d11dc","observation_id":"5da52a67-2b9b-4025-9e75-2c93446b6fa1","resolution":{"observed_at":"2026-08-14T11:34:23.797269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.781379Z","title":"Exact matrix completion via convex optimiza- tion,","venue":null,"work_id":"a39b05dd-d606-48f1-acbd-9ec1c5ed8514","year":2009},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.903059Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:3cd4a3c202aff5269c8637c1a7f9b9afc7d4217be552aef95a65c7d1e63b8752","observation_id":"ab1fc881-c375-420b-b9de-ff48eb55d684","resolution":{"observed_at":"2026-08-14T11:34:23.785223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.769176Z","title":"Spectral regularization algo- rithms for learning large incomplete matrices,","venue":null,"work_id":"59bd56bc-9082-47fe-ae91-49eba733fbc9","year":2010},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.906999Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:dc46e3a57caf36217ad3e4ca9fe0ead21c322f833b71de8601b856ee6a541618","observation_id":"14d1e9a5-09ef-4c5b-99be-4b7a8f1d51e7","resolution":{"observed_at":"2026-08-14T11:34:23.773239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.756897Z","title":"Penalized regressions: The bridge versus the lasso,","venue":null,"work_id":"6a5d505a-bfb4-4674-9ffc-afcf943826f3","year":1998},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.910615Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:19d5a80363453f3677880563e0f2ca344de0600e38f9f4ab876a5261a57b300e","observation_id":"127c5791-d023-49f6-8b95-30afb60b598f","resolution":{"observed_at":"2026-08-14T11:34:23.761053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.744714Z","title":"Block-relaxation algorithms in statistics,","venue":null,"work_id":"01c147aa-ecde-4ad4-88f1-efb5c287fc53","year":1994},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.914316Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:30d41647c0017593568382b57d2bb4249ee4e070cd2269bc64eaf2ca92e14138","observation_id":"a3d8a670-3288-45de-baf2-6ae6bb2c8b71","resolution":{"observed_at":"2026-08-14T11:34:23.748639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.732225Z","title":"A tutorial on MM algorithms,","venue":null,"work_id":"d854b845-86ab-45c4-b137-f9cf9b349d54","year":2004},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.918223Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:2d7bce437668f2969aab151fe17c92bf90e1a67c327f5e10d8b1b35ba07774d1","observation_id":"20ed9e9c-ab92-48a7-b5e1-58f1b377e04b","resolution":{"observed_at":"2026-08-14T11:34:23.735885Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.720388Z","title":"Weighted least squares ﬁtting using ordinary least squares algorithms,","venue":null,"work_id":"4c79bdfc-9589-48c8-990d-463b79f17ebe","year":1997},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.921830Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:a9e4cba3cb2825753e1506b96cdf5c00a2d6235208626ef26e131ab2c917f0c3","observation_id":"8e4a225b-6a4b-43ac-a110-bed205e235a4","resolution":{"observed_at":"2026-08-14T11:34:23.724258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.708415Z","title":"Boyd and L","venue":null,"work_id":"6dad5e5b-0371-4b7d-8ac3-be7a2a5c03f4","year":2004},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.925348Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:2f3b5ae880038c740a1f64e6e64f06ebbb1b6e16cb716bbca0435aae2cbe617a","observation_id":"f3a76ab3-b94c-414e-b008-f5e4e9d5ae78","resolution":{"observed_at":"2026-08-14T11:34:23.712339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.696041Z","title":"Generalized singular value thresholding,","venue":null,"work_id":"dbe00199-fe31-4799-b607-b6eb57ec160c","year":2015},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.929121Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:f716025e6cba2623502d447a24a78eafcd993152a61b8b7d3fa7bf2a420929bf","observation_id":"80679c9d-8992-46c0-a65d-d37188ca1fb4","resolution":{"observed_at":"2026-08-14T11:34:23.699901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.684017Z","title":"Le Cam and G","venue":null,"work_id":"86e4f117-b838-4639-a42c-012eb6012d7f","year":2012},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.933033Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:633071f1620886da311b4d5fe1890279d0304ebc639f88a8be883a7fe029a8cb","observation_id":"a90d6ee4-b0f2-4220-9ff8-2f65dd3761b7","resolution":{"observed_at":"2026-08-14T11:34:23.687649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.04982","last_updated":"2019-06-03T09:04:35Z","snapshot_observed_at":"2026-08-14T18:52:23.815543Z","submitted_at":"2018-07-13T09:31:46Z","title":"Generalized simultaneous component analysis of binary and quantitative data","version":3},"cited_work":{"arxiv_id":"1807.04982","doi":null,"metadata_source":"pith","pith_arxiv_id":"1807.04982","snapshot_observed_at":"2026-08-14T11:34:23.195773Z","title":"Generalized simultaneous component analysis of binary and quantitative data","venue":"stat.ME","work_id":"6a1c5dae-1fce-4539-8137-762afcd25bbd","year":2018},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.936780Z"},"links":{"cited_paper":"/paper/1807.04982","citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:838b3508de2e486574dd8b32f6da7ddf9641c09e75747851c809198b03273787","observation_id":"7dd73dde-382e-46a8-b7fc-dbbedcba5243","resolution":{"observed_at":"2026-08-14T11:34:23.200715Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.671974Z","title":"A structured overview of simultaneous component based data integration,","venue":null,"work_id":"aae35a0a-4287-4198-a64f-1d586e68625f","year":2009},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.940743Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:b946faf467c3edb94147c32cc87243284210275225f148d2d95fd4253f4e5d23","observation_id":"f9dc82d5-f8f6-4386-b593-31370f65c979","resolution":{"observed_at":"2026-08-14T11:34:23.676080Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.659828Z","title":"Integrating functional genomics data using maximum likelihood based simultaneous component analysis,","venue":null,"work_id":"4af6cd06-ca96-49eb-a038-ab582bcf457f","year":2009},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.944386Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:6646085d6f9e08fc3aed5a48b94137d83ec759b61fa8e7ccb4194fb065490f84","observation_id":"6630a1d7-d9dd-4f51-aa2a-8eef80912696","resolution":{"observed_at":"2026-08-14T11:34:23.663643Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.647359Z","title":"Pattern discovery and cancer gene iden- tiﬁcation in integrated cancer genomic data,","venue":null,"work_id":"e9fe8a6a-7c18-4d4c-a86f-2017866a08ee","year":2013},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.948389Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:e5c6c5a72345d82954009352efa5c6019c96b70132c645efd704ddee01d5aa46","observation_id":"0d7e6483-6f11-48d2-a2d9-2cb40cafde83","resolution":{"observed_at":"2026-08-14T11:34:23.651453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.634698Z","title":"A generalization of princi- pal components analysis to the exponential family,","venue":null,"work_id":"4b83eed3-1cf3-4ffa-85f7-07b9982d2bea","year":2002},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.952213Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:5004c98ea8ed029927361ca67f80643037f8b13aa5f10ba20a3779af1b86e212","observation_id":"e4925b52-c45c-4311-9c8c-49484b3c9722","resolution":{"observed_at":"2026-08-14T11:34:23.638744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.621898Z","title":"Nuclear-norm penaliza- tion and optimal rates for noisy low-rank matrix completion,","venue":null,"work_id":"dfc2d462-94ca-4166-abb7-b19dcf56c938","year":2011},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.956242Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:cab0b16c8792c82d63ec6d12714e24c1bbbcf759173a04506c4f31276beb5172","observation_id":"b1f65e55-1194-4012-9824-e24701cd6e09","resolution":{"observed_at":"2026-08-14T11:34:23.626001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.609193Z","title":"Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: Application to cancer molecular classiﬁcation,","venue":null,"work_id":"5cd3f031-2e37-4da6-9a6f-903f33f4130e","year":2015},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.960079Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:ce76f60d8c069fe4da88912ddac17331eeaa61ac977c31b304222b6233bc4ce6","observation_id":"d11781c7-d58f-4de4-b8bf-3d8b8fadcc34","resolution":{"observed_at":"2026-08-14T11:34:23.613150Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.595910Z","title":"Cross-validation of component models: A critical look at current methods,","venue":null,"work_id":"a239734d-65be-4015-9336-a9a9f36cc53d","year":2008},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.963905Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:1d979e962b62280b04b56d8267d05b6b05127010081e64ad2c26e5d7e3cbb347","observation_id":"ca8b6747-cb68-45fb-8941-9424e2a92af3","resolution":{"observed_at":"2026-08-14T11:34:23.600046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.583507Z","title":"Support vector machines with adaptive Lq penalty,","venue":null,"work_id":"6198114b-38e2-4ea2-bb7b-42948d8c722d","year":2007},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.967652Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:f290edc99dd65c121f258939b4c8c7f660910eb6a44b6d4627b37ffffd77b131","observation_id":"f6a718c6-ad3d-4ff9-95c9-e2fb48fa32b1","resolution":{"observed_at":"2026-08-14T11:34:23.587335Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.571092Z","title":"Principal component analysis of binary genomics data,","venue":null,"work_id":"ac84e9e7-95f0-4f9b-a9dc-9078f8ca40ed","year":2017},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.971367Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:fcbb5b7918e9993106871933f82a6c5424c8f56cd02a67c348e558d97deac010","observation_id":"9abbaf6a-967c-44b9-ae8c-61c801528e10","resolution":{"observed_at":"2026-08-14T11:34:23.575280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.558625Z","title":"Genomic classiﬁca- tion of cutaneous melanoma,","venue":null,"work_id":"b7737cac-76da-47b5-a126-2d04687f13bd","year":2015},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.975128Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:81a716b65701b31cfe65b66facfa67a73e711554377a017864721ac264894a0e","observation_id":"a5af6aca-3115-498a-8802-f8f9d6594c06","resolution":{"observed_at":"2026-08-14T11:34:23.562548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.546532Z","title":"Comprehensive molecular proﬁling of lung adenocarcinoma,","venue":null,"work_id":"bdea4133-087d-4b24-8abb-2b18992bf3a7","year":2014},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.979071Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:1ac97081a980c4841aae21a54a6e599d7a486324b0b51855de0baecdbbe64abb","observation_id":"5cf65e71-5bd4-4214-9d23-be4506c75d1b","resolution":{"observed_at":"2026-08-14T11:34:23.550240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.534247Z","title":"Comprehensive molecular portraits of human breast tumours,","venue":null,"work_id":"7671c660-2328-477f-b09f-8c69d71dec66","year":2012},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.982756Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:01676c67b6b301d6886864f87379de763a3c0c5d1d7dae4962b6c789868379c2","observation_id":"e79ed25c-fe8c-4a2e-918d-ab56f7b04cbe","resolution":{"observed_at":"2026-08-14T11:34:23.538032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.521171Z","title":"iTOP: Inferring the topology of omics data,","venue":null,"work_id":"d3817a2b-2ed7-47ec-9ebf-723e1baf3bc2","year":2018},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.986263Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:16bb717ab474a4730af887f037d9fa3f4a7bb484c924320d23a78592c94bac8a","observation_id":"fb4467d4-ce51-4862-a089-cedd833b9aca","resolution":{"observed_at":"2026-08-14T11:34:23.525145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.508890Z","title":"Learning the structure of mixed graphical models,","venue":null,"work_id":"c7e48d44-83ac-4cb1-b5cf-889ee28a021c","year":2015},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.989845Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:fb09b2f73a7ed272825ac7a56be717d177ae6e2a3ea23a17acf5187b48c349f3","observation_id":"68fa3aa1-e0d1-4b55-8bbf-ff85133f4273","resolution":{"observed_at":"2026-08-14T11:34:23.512693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.495977Z","title":"High-dimensional mixed graphical models,","venue":null,"work_id":"97d39fab-f592-4a9f-9529-2019481051ae","year":2017},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.993717Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:13de95656729bf30a1c64f014d50a2ce9d5774a768c4d891e010da845ad360ad","observation_id":"598be29c-d6fd-42c5-991b-9970ca363d09","resolution":{"observed_at":"2026-08-14T11:34:23.499802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.483899Z","title":"Integrative clustering of multiple genomic data types using a joint latent variable model with application to breast and lung cancer subtype analysis,","venue":null,"work_id":"0a806965-93f1-49ae-8fbb-289c97f71e59","year":2009},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:22.998051Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:eb3cced6f97f3e092a3cdf9166ab95640b41b4bd0c733b162ccbdbe604c967ee","observation_id":"5cc78fcb-0b11-4aa3-abd7-c4be5608f56d","resolution":{"observed_at":"2026-08-14T11:34:23.487803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.471588Z","title":"Separating common from distinctive variation,","venue":null,"work_id":"5c49387d-cb3e-4d11-8b23-8add5ec6d248","year":2016},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.001559Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:4f0429937ae0845f2492fa01bdb42f8554a345d4e27d19843bdee8fdafaea730","observation_id":"4d0558d6-4c31-4f89-a80f-95bcb0a1506f","resolution":{"observed_at":"2026-08-14T11:34:23.475655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.458871Z","title":"Joint and individual variation explained (JIVE) for integrated analysis of multiple data types,","venue":null,"work_id":"2620920b-05b0-4272-8309-84f1431098a8","year":2013},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.005157Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:957793361f1df1bdce758051da3e96b6706a5b7bf0c7155eacdb9dc93508a223","observation_id":"5d6b05bc-6c2b-4cff-a748-1dd696e7ca9d","resolution":{"observed_at":"2026-08-14T11:34:23.462912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.446005Z","title":"Global, local and unique decom- positions in OnPLS for multiblock data analysis,","venue":null,"work_id":"a4453197-06fb-46ba-999f-6ddbb7bc25aa","year":2013},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.008999Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:4a49fc66c9a8d8bacd7e9a12a89372942651a0cc4d33572ef233c6a1663c0a69","observation_id":"f87d3af0-3652-42b8-923a-13acc1c36356","resolution":{"observed_at":"2026-08-14T11:34:23.450198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.432701Z","title":"Performing DISCO-SCA to search for distinctive and common information in linked data,","venue":null,"work_id":"0a98d396-c47b-4786-ad61-f49cf289456a","year":2014},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.012575Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:43bd1ea0fbb3cd87891cb7b0ef5514f295d27ac7ea33d9647908df1295fc0f68","observation_id":"f1265812-932b-4132-bb8a-987ca200719b","resolution":{"observed_at":"2026-08-14T11:34:23.436810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.419473Z","title":"Preference mapping by PO-PLS: Separating common and unique information in several data blocks,","venue":null,"work_id":"333fd159-6285-40de-b5a3-5dfc68bce4f5","year":2012},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.016163Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:828b050a2453c01dfedb72316b7eed8ae93f66b57ddfd68069f0dba13968bc84","observation_id":"4d7b6211-87cf-444a-9cb4-aa1a5d902e92","resolution":{"observed_at":"2026-08-14T11:34:23.423857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.406796Z","title":"Performance of meth- ods that separate common and distinct variation in multiple data blocks,","venue":null,"work_id":"f71b4260-c148-43c2-8ca1-9933adc5adc1","year":2018},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.019887Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:f499a7e179d292bf0663daa4cc30cd4a8cf7c7beca0ea3f5fca78a365ea11dff","observation_id":"4194da99-c03c-4bd5-9519-bf5e5dbaf5d8","resolution":{"observed_at":"2026-08-14T11:34:23.410731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.393628Z","title":"Group factor analy- sis,","venue":null,"work_id":"fcfc123c-9652-4804-bfaf-711e0c6c8ef4","year":2015},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.023552Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:ee26dc2a7c3f4d547d3944ac860b9c9a88368e046baa9590ee27b918f006dc8a","observation_id":"98762622-bc16-4e63-aec6-ba4010c60fdf","resolution":{"observed_at":"2026-08-14T11:34:23.397534Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"0909.3052","last_updated":"2009-09-16T16:16:48Z","snapshot_observed_at":"2026-08-15T05:38:56.446645Z","submitted_at":"2009-09-16T16:16:48Z","title":"Cross-Validation for Unsupervised Learning","version":1},"cited_work":{"arxiv_id":"0909.3052","doi":null,"metadata_source":"pith","pith_arxiv_id":"0909.3052","snapshot_observed_at":"2026-08-14T11:34:23.178663Z","title":"Cross-Validation for Unsupervised Learning","venue":"stat.ME","work_id":"351d5f18-afd8-44c3-921c-8e8a6aca4c6c","year":2009},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.027342Z"},"links":{"cited_paper":"/paper/0909.3052","citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:d1457be1ea0ab6506991bd4dade22c82a135e9a0c5deef19e4b674fef9cb7fad","observation_id":"ae70761b-3282-49fb-a9f8-aca647e7f4ab","resolution":{"observed_at":"2026-08-14T11:34:23.182683Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.381324Z","title":"Multi-Omics Factor Analysis—a framework for unsupervised integration of multi-omics data sets,","venue":null,"work_id":"27eaafec-d3b9-451b-8e7e-80efe0784979","year":2018},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.031234Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:7190c95afe9b01e8a00d1c56152518c1268a2e95bfa7fc9a24dd8df4b264a729","observation_id":"91205a5f-5e32-41c8-bef3-8c7321941df8","resolution":{"observed_at":"2026-08-14T11:34:23.385295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.369133Z","title":"High-dimensional graphs and vari- able selection with the lasso,","venue":null,"work_id":"dce68cef-4673-43dd-a62e-f9954e07d82d","year":2006},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.035002Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:61389b42e3f07327c5f3e828fcaedf1830f83280fb8dad475c1e951a9fb86d79","observation_id":"c6879e00-03a4-4b96-a594-6df920a39626","resolution":{"observed_at":"2026-08-14T11:34:23.373090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.356427Z","title":"A note on the lasso and related procedures in model selection,","venue":null,"work_id":"9c884e1f-16ad-4eb5-832b-e10003ca1aeb","year":2006},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.038738Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:a99341d9f63fc446f486dd773d805ac02b3a2c8b28dc5e62bc9cc512f56233ae","observation_id":"dc2977c6-d98d-4b56-9829-78ce3852074b","resolution":{"observed_at":"2026-08-14T11:34:23.360263Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.344209Z","title":"Drug-perturbation- based stratiﬁcation of blood cancer,","venue":null,"work_id":"f97bb9d3-4f5b-4136-a40c-86a88dcdbd2c","year":2018},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.042399Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:cc1fc991bc28dec3d2e50ca063e68d85bb1ba11559c664335bf359dc9bd609a9","observation_id":"4583861a-4e8a-4cfa-bf14-2caaef3e00f6","resolution":{"observed_at":"2026-08-14T11:34:23.348049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.331713Z","title":"A ﬂexible framework for sparse simultaneous component based data integration,","venue":null,"work_id":"4141cdc5-1517-49b6-8415-dddd70b3338a","year":2011},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.046258Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:a22b6b382542124c73b890051f338c454f279a4b83cd25580507896a30f9cbba","observation_id":"6b23bb50-7757-43f1-9ec0-2fb57be4c19c","resolution":{"observed_at":"2026-08-14T11:34:23.335546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.319344Z","title":"Data fusion in metabolomics using cou- pled matrix and tensor factorizations,","venue":null,"work_id":"6387a5dd-29f4-4497-ac39-be23b92db802","year":2015},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.049892Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:c6f24fb587f530fea3fbe31830395c211713780d2dbe6bee8ce17b7793ef4dda","observation_id":"c9469d57-82a7-423a-8b05-2bc8735809ea","resolution":{"observed_at":"2026-08-14T11:34:23.323230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.09486","last_updated":"2019-02-25T18:03:11Z","snapshot_observed_at":"2026-08-15T21:51:02.678374Z","submitted_at":"2019-02-25T18:03:11Z","title":"Logistic principal component analysis via non-convex singular value thresholding","version":1},"cited_work":{"arxiv_id":"1902.09486","doi":null,"metadata_source":"pith","pith_arxiv_id":"1902.09486","snapshot_observed_at":"2026-08-14T11:34:23.159561Z","title":"Logistic principal component analysis via non-convex singular value thresholding","venue":"stat.ME","work_id":"025d29ee-f4c4-4e62-a79f-7d2b280ad11f","year":2019},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.053550Z"},"links":{"cited_paper":"/paper/1902.09486","citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:c6881883985af0453f30f9be627e9ec4ff4aa4113b194f381bfd01a481858141","observation_id":"19a5153d-100f-44ba-bf62-7320e1419f68","resolution":{"observed_at":"2026-08-14T11:34:23.163872Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.305667Z","title":"Gelman, H","venue":null,"work_id":"94636d6c-3e49-421b-a01a-c66b0108e63b","year":2013},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.057576Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:57938c172e441afc577d26b763e449fc9e82663f79c8b9fc9fe91cc06beb2138","observation_id":"69492c8d-fe95-4793-a38f-51f42725a6f8","resolution":{"observed_at":"2026-08-14T11:34:23.310202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.291079Z","title":"Ma- trix correlations for high-dimensional data: the modiﬁed RV-coeﬃcient,","venue":null,"work_id":"35b9f8bf-9022-4cdb-ad12-e0b1d55e4006","year":2008},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.061377Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:dfda22cb6d0e47e6a7bd415bb92be35780e79f1c3ba8a533d0a869eeffd11cf1","observation_id":"ef9201d9-b4ff-471e-962f-021b94da3bc9","resolution":{"observed_at":"2026-08-14T11:34:23.295442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.02811","last_updated":"2018-07-08T13:06:26Z","snapshot_observed_at":"2026-08-13T17:25:53.968899Z","submitted_at":"2018-07-08T13:06:26Z","title":"A Tutorial on Bayesian Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.02811","snapshot_observed_at":"2026-08-14T11:34:23.065245Z","title":"A tutorial on bayesian optimization,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.065245Z"},"links":{"cited_paper":"/paper/1807.02811","citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:3c327d0156951d9979f1c2af61124c3dbc39261fd9062f0eb1c8efb8c3149fe0","observation_id":"61773801-ab32-4626-ac24-0d2ffe5b447f","resolution":{"observed_at":"2026-08-14T11:34:23.065245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.278722Z","title":"Practical bayesian optimiza- tion of machine learning algorithms,","venue":null,"work_id":"52dffe05-fb03-443c-b664-207448fd5e75","year":2012},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.071214Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:b82bd3bd2a41248506efd80f53f7f6ece552e3a33461ad07c836192f64400ba0","observation_id":"43453b65-932d-4950-bdf9-028865dfdd8f","resolution":{"observed_at":"2026-08-14T11:34:23.282670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:34:23.266031Z","title":"Distributed optimization and statistical learning via the alternating direction method of multipliers,","venue":null,"work_id":"c7d9ad0a-9595-4431-90fb-ab6ae0692753","year":2011},"citing_paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-14T11:34:23.075134Z"},"links":{"citing_paper":"/paper/1908.09653"},"observation_digest":"sha256:f9a4f23f846aac75a11b87c8306c2cf5bea9fa7cfcdb255e11333c850c76d5f0","observation_id":"ea062503-ca56-42e0-a6f5-8925816a635d","resolution":{"observed_at":"2026-08-14T11:34:23.270196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.09653","last_updated":"2019-08-23T12:20:04Z","latest_version":1,"primary_category":"q-bio.GN","snapshot_observed_at":"2026-08-15T12:23:29.072896Z","submitted_at":"2019-08-23T12:20:04Z","title":"Fusing heterogeneous data sets"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":30,"verified_exact":3,"verified_fuzzy":67},"total_outbound_references":103},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 100 of 103 outbound references and 0 inbound Pith citation observations for arXiv:1908.09653."}