{"as_of":"2026-08-16T11:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a08276bc0df23a1dd2b47002ffa4184b343d32329c66999ccd2e63d6370a11f1","coverage":[{"denominator":18,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":18,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:47:30.929785Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/1908.06497/citation-record","integrity":"/paper/1908.06497/integrity","json":"/paper/1908.06497/citation-record.json","paper":"/paper/1908.06497"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:47:31.392278Z","title":"A constrained procrus tes problem","venue":null,"work_id":"d96c06f7-3d65-40a9-be44-1412eebc285d","year":1997},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.819853Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:50118b36b13e784f0ee95f526d8d6c8551c24b5ec51fbbd8dfc1ef8149175d6b","observation_id":"2806387e-0c7e-423f-8389-34390d1ef486","resolution":{"observed_at":"2026-08-14T12:47:31.399526Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1407.3894","last_updated":"2014-09-18T14:29:22Z","snapshot_observed_at":"2026-08-14T23:26:44.093626Z","submitted_at":"2014-07-15T06:46:38Z","title":"Efficient Algorithms for Positive Semi-Definite Total Least Squares Problems, Minimum Rank Problem and Correlation Matrix Computation","version":2},"cited_work":{"arxiv_id":"1407.3894","doi":null,"metadata_source":"pith","pith_arxiv_id":"1407.3894","snapshot_observed_at":"2026-08-14T12:47:30.986094Z","title":"Efficient Algorithms for Positive Semi-Definite Total Least Squares Problems, Minimum Rank Problem and Correlation Matrix Computation","venue":"math.OC","work_id":"a36a56be-76ac-49ed-a6e5-7ddab1b33cae","year":2014},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.826199Z"},"links":{"cited_paper":"/paper/1407.3894","citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:18ae8b3d6bdef1d5ac959fd8fe362c33ae3ef2de5ccdb57c06d70e3bb5b2d18a","observation_id":"622aa32d-d9b6-46eb-bec3-c6554d4f9f72","resolution":{"observed_at":"2026-08-14T12:47:30.994168Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.348010Z","title":"Two-point step size g radi- ent methods","venue":null,"work_id":"58e6e1f0-bd36-43de-b3a3-c23bf079fe5d","year":1988},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.832294Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:57d0e0b35d1ebd35b08fc69ed7bf48ca50f010b22197e35bf90e9beb74039463","observation_id":"97e0015d-3126-4fd1-8f86-f18205788b7a","resolution":{"observed_at":"2026-08-14T12:47:31.354137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:47:30.838066Z","title":"Nonlinear programming","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.838066Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:a41ea2dae3327eed8cb35cd3552ae9d41b2a6dad0754a20e2dd7fab21f0dc8d1","observation_id":"e73607ce-8155-4895-b21d-920e33f5ed6a","resolution":{"observed_at":"2026-08-14T12:47:30.838066Z","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":"2026-08-14T12:47:31.302911Z","title":"Optimal matrices describing linear systems","venue":null,"work_id":"aeef9216-fccd-4b17-a772-bc103683dc6f","year":1968},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.845473Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:f6ca48593f5b9767795014b5e9de5f3963df73bee54e3ff7cddaa1f5ee8b89f7","observation_id":"aea0b7e2-be4d-46c2-be0b-7847f4c20ea3","resolution":{"observed_at":"2026-08-14T12:47:31.313956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.269948Z","title":"Projected barzilai-borwein me th- ods for large-scale box-constrained quadratic programming","venue":null,"work_id":"2f5ea853-dcfb-4bff-afe8-8b2dcc100d8d","year":2005},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.853129Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:cd0aefbb217c9e4f9b434b6afddd5d5275015e6e42164cb977c6b7300722a163","observation_id":"2853603e-4c36-4083-bcf1-648c0e4e7578","resolution":{"observed_at":"2026-08-14T12:47:31.281723Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.239408Z","title":"Non- monotone algorithm for minimization on arbitrary domains with appli- cations to large-scale orthogonal procrustes problem","venue":null,"work_id":"49a1b123-9182-4e3e-aa99-3fc999db0b4a","year":2017},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.860575Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:ea61317b82c130800a33e1f781af3ccf81597880a81e4ce788b692a73f6820ec","observation_id":"66979a11-56f7-4b52-b39d-92415e1a8a10","resolution":{"observed_at":"2026-08-14T12:47:31.247727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.215090Z","title":"A semi-analytical approach for the positive semideﬁnite procrustes problem","venue":null,"work_id":"6006595e-7e94-4ad9-b7e8-cf50f3f31922","year":2018},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.866068Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:4d4f19861a643b481bd0cffaf0add5e941fcecfd50287f588094b0b05c987201","observation_id":"71105c8f-6dcd-40c9-bc0b-7b6f2cdfb35d","resolution":{"observed_at":"2026-08-14T12:47:31.222279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.194678Z","title":"Computing a nearest symmetric positive semideﬁ - nite matrix","venue":null,"work_id":"c17a98cf-5723-4236-84c2-735a07041a3d","year":1988},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.872102Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:e1899b354b1409c80f2e9f750a64408b6d316c424a6f20282da5ee45db17604e","observation_id":"f5ff1597-337a-496a-9aee-293658ae50a7","resolution":{"observed_at":"2026-08-14T12:47:31.201586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.173588Z","title":"Least-squares solution of ax b= d over symmetric positive semideﬁnite matrices x","venue":null,"work_id":"12696045-1312-4109-9117-0d32a2b7f4d6","year":2003},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.877673Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:a7c02d2515ccea762a1e3d535678228125ad94f44dcfe86b6bb487292796d293","observation_id":"56c9a17c-be7f-4d02-a2b8-9d2915bbad89","resolution":{"observed_at":"2026-08-14T12:47:31.180753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.152138Z","title":"Introductory lectures on convex programm ing volume i: Basic course","venue":null,"work_id":"e19c09ec-4052-4165-82f1-59f276a90af2","year":1998},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.885121Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:21aad65ec66f8fe14d84edd495c6c2a734ec370ff92efb8ef8e0faf25877f07e","observation_id":"13cb8516-ad30-4223-8afb-b11ae60d6fa9","resolution":{"observed_at":"2026-08-14T12:47:31.159258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:47:30.890360Z","title":"Numerical optimization","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.890360Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:217c5aba40012deef65160956da09fd17aad3a3ecb9ce0a24063225b33a16306","observation_id":"22e9a87c-6538-4df4-a24e-b9604c84f7a6","resolution":{"observed_at":"2026-08-14T12:47:30.890360Z","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":"2026-08-14T12:47:31.119811Z","title":"The barzilai and borwein gradient method for t he large scale unconstrained minimization problem","venue":null,"work_id":"0ff72038-b0f4-4002-9886-d3c12bd4b528","year":1997},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.895612Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:b05a1e57c0fddb3c875b88f0918961780d3ef8e255f001c7c198af12bb928081","observation_id":"87929a2a-b84e-4c72-9df9-cf5a5c5b1f80","resolution":{"observed_at":"2026-08-14T12:47:31.125287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.097972Z","title":"Approximation by a hermitian positive semideﬁnite toeplitz matrix","venue":null,"work_id":"66ae23a7-0e5d-43f2-9ca5-b5650a9ec225","year":1993},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.903401Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:eef99fa0421b014343399e94aaf8b65d8410aec107f992f5591acb7508798017","observation_id":"d912eacc-5cc6-43bf-90a9-381d8d974b24","resolution":{"observed_at":"2026-08-14T12:47:31.104069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.077381Z","title":"An inexact primal–dual path following algorithm for convex quadratic sdp","venue":null,"work_id":"39910080-b446-49da-8298-2ea8b2b4ed47","year":2008},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.910901Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:d465eb791d1f2ce3f1fe5d6ac59cf768335c4b4bc179f0023829c0f73fa996b0","observation_id":"119894b5-90d4-4799-8c93-d0d3566bd400","resolution":{"observed_at":"2026-08-14T12:47:31.083198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.055762Z","title":"Sdpt3a matlab software package for semideﬁnite programming, version 1.3","venue":null,"work_id":"d977dd96-8a26-4439-b001-33c7568ee63b","year":1999},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.917248Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:3bb6a7e96587d940d0874e589978943138252499c03e38ed3edb8100db27e5c2","observation_id":"01bff190-387c-4fed-a576-9012ab8b8176","resolution":{"observed_at":"2026-08-14T12:47:31.062139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.034257Z","title":"Least-squares solution of f= pg over positiv e semideﬁnite symmetric p","venue":null,"work_id":"eaebe434-33cd-472a-82db-6f7c13ebc99f","year":1996},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.922624Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:636bb8e4dc9c961dc045b848b932df889b1a0230d5048e37ab29e2e7f86b2944","observation_id":"7ad2027d-dca9-4906-8573-b7ea0821f42b","resolution":{"observed_at":"2026-08-14T12:47:31.040600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:47:31.012196Z","title":"A nonmonotone line search technique and its application to unconstrained optimization","venue":null,"work_id":"3d6788bb-f580-447d-bbed-b3beb8df220a","year":2004},"citing_paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:47:30.929785Z"},"links":{"citing_paper":"/paper/1908.06497"},"observation_digest":"sha256:c12b23bac2a2800c84e780554f33f521483f94d1a3d4472e82ac484be28eeaa5","observation_id":"2b2be216-0e28-4f71-81ce-26627d13f003","resolution":{"observed_at":"2026-08-14T12:47:31.018233Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.06497","last_updated":"2019-08-18T18:40:58Z","latest_version":1,"primary_category":"math.NA","snapshot_observed_at":"2026-08-16T08:17:59.862122Z","submitted_at":"2019-08-18T18:40:58Z","title":"A Spectral Gradient Projection Method for the Positive Semi-definite Procrustes Problem"},"reference_resolution":{"displayed":18,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":1,"verified_fuzzy":15},"total_outbound_references":18},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:1908.06497."}