{"as_of":"2026-08-08T16:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d1715ccb87c8f46192f3a9553c2f7276119d3f0d8250c41697df479808f3c993","coverage":[{"denominator":30,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":30,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T19:18:39.364955Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T10:38:19.251502Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.06061","snapshot_observed_at":"2026-07-11T10:38:19.251502Z","title":"Estimating prevalence with precision and accuracy","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04977","last_updated":"2026-07-06T12:12:16Z","snapshot_observed_at":"2026-08-06T03:55:21.304753Z","submitted_at":"2026-07-06T12:12:16Z","title":"Geometry-Aware Bayesian Quantification via Compositional Data Analysis","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-11T10:38:19.251502Z"},"links":{"cited_paper":"/paper/2507.06061","citing_paper":"/paper/2607.04977"},"observation_digest":"sha256:fb42e52bbdc4d3d07dcecc7c489d2bf3b2f0ac9cffffad022322df8b29933a23","observation_id":"2799ab98-eeb2-4fdf-9e7e-7a86c6734c25","resolution":{"observed_at":"2026-07-11T10:38:19.251502Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2507.06061/citation-record","integrity":"/paper/2507.06061/integrity","json":"/paper/2507.06061/citation-record.json","paper":"/paper/2507.06061"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/11564096_55","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:03:56.115653Z","title":"Counting positives accurately despite inaccurate classification","venue":"Lecture notes in computer science","work_id":"04ee6beb-5429-4a01-8843-373fbd25b76f","year":2005},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:36.335109Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:d2fcc10971775c048b15965d4ff8a107c2a3363ac3de51a1e9b01d29f6ba81b1","observation_id":"9c9199e5-1574-450a-a1be-1d4959801407","resolution":{"observed_at":"2026-08-06T19:18:41.866019Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10618-008-0097-y","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:41.353882Z","title":"Quantifying counts and costs via classification","venue":null,"work_id":"e3796531-f962-478f-8a97-23c04d39f3a2","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:36.414812Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:3b794c6b9cd3a8ccf94979a6f7e7e705a5653f2ab3c90fa7a9ff6f30c11db17b","observation_id":"11ac1edd-c7e4-4dee-ade2-2238825d4b3d","resolution":{"observed_at":"2026-08-06T19:18:41.523031Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s10618-013-0308-z","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:41.069476Z","title":"Ag- gregative quantification for regression","venue":null,"work_id":"6a83bb8b-fa02-432e-8e2d-a9c1a6f29c20","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:36.500276Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:a12e42cfc0b97ac605996484d518b26cecf8df76f99bb6931d77310d4db6c6f8","observation_id":"dcba73db-a235-4a97-9752-bd91fc0be52e","resolution":{"observed_at":"2026-08-06T19:18:41.222773Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s13748-016-0103-3","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:40.670635Z","title":"Why is quantification an interesting learning problem? 6(1):53–58","venue":null,"work_id":"a06a1d84-24a3-4ff0-ad1d-0926815f89e6","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:36.606716Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:ff9424ce5bf0363471154bfd2dd6d1be5af2191488ad65d0b80a82e37e728f67","observation_id":"57be76ba-2fdd-4a6f-9400-1f0391ce524e","resolution":{"observed_at":"2026-08-06T19:18:40.848249Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:36.772667Z","title":"Learning to Quantify, volume 47 of The Information Retrieval Series","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:36.772667Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:a764a5ca76b6d8988d29a1bbefcb3e37d5f1723912eabe33f7196b2999ca9d81","observation_id":"e390e3b6-9c41-4b4a-b529-d80ecc0ec5a3","resolution":{"observed_at":"2026-08-06T19:18:36.772667Z","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":"10.3390/make1030047","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:40.436353Z","title":"Confidence intervals for class prevalences under prior probability shift","venue":null,"work_id":"8dd7f948-5956-496f-acdd-b1f9c3f8740d","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:36.889156Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:61c5c3a4490b1014629c2875dda5115c7ca002699e02893d542cc5d6d082406f","observation_id":"e2142356-8c50-428e-b6f1-8fd550ea92a1","resolution":{"observed_at":"2026-08-06T19:18:40.578869Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:44.824673Z","title":"When training and test sets are different: Characterizing learning transfer","venue":null,"work_id":"92f63620-abd4-4ca1-a52a-99266518fd3e","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.030337Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:f0ef214a19538521d0219b482a2716f0bf814c0d57d6300bac247ffe3a61dca8","observation_id":"c5a6db3f-d73b-4db7-ae7b-8e26ca6bcf6b","resolution":{"observed_at":"2026-08-06T19:18:44.928891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:37.144278Z","title":"URL https://doi.org/10.7551/ mitpress/9780262170055.003.0001","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.144278Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:599db8e7062c9d2d6006df11cedb06cb5463ed43eee3823b6b84eb5753763904","observation_id":"bde0deb1-8630-4e00-94e9-bef4140c86a1","resolution":{"observed_at":"2026-08-06T19:18:37.144278Z","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":"2026-08-06T19:18:44.559264Z","title":"Bayesian quantification with black-box estimators","venue":null,"work_id":"4d225eaf-b196-48f6-b23b-828bf07a9d68","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.224606Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:2b1769d35b7708907f553114a56ff0a9676e94ea917056f7c30573da0107f72f","observation_id":"1e6b56d4-bdc5-40b4-8339-45df60146d09","resolution":{"observed_at":"2026-08-06T19:18:44.725110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:37.336277Z","title":"Uncertainty-aware generative models for inferring document class prevalence","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.336277Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:1bd8a37d707839ea2f5ecc69ce2eb9dba3c474627373be1992fe95d3a923cb91","observation_id":"54d4e12f-c96a-4cd1-a48e-52a4422cca2a","resolution":{"observed_at":"2026-08-06T19:18:37.336277Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-06T19:18:37.481670Z","title":"Asif Naeem","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.481670Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:8d1eb0103bc1f21ef9fb4be44b9783d3c1fc8c4979321bbcec6fb0c25bb26ebe","observation_id":"607a3133-0dc7-4d07-92da-d314be0c42f2","resolution":{"observed_at":"2026-08-06T19:18:37.481670Z","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":"2026-08-06T19:18:37.573261Z","title":"Generalized bayes quantifica- tion learning under dataset shift","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.573261Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:137fd55d1d9e18ace47e614a804871e83fd6d729ef00b3087e819121a4ff430a","observation_id":"60712cc3-c6db-4142-bd50-5473bc000f10","resolution":{"observed_at":"2026-08-06T19:18:37.573261Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.03916","last_updated":"2018-07-26T12:51:37Z","snapshot_observed_at":"2026-08-04T00:11:09.553000Z","submitted_at":"2018-02-12T07:16:03Z","title":"Detecting and Correcting for Label Shift with Black Box Predictors","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.03916","snapshot_observed_at":"2026-08-06T19:18:37.753788Z","title":"Lipton, Yu-Xiang Wang, and Alex Smola","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.753788Z"},"links":{"cited_paper":"/paper/1802.03916","citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:0c5dd4960112081837ed0236c209d6f0fa4d16241a3c5fac50a88649e29c263c","observation_id":"6227f5ad-e256-470f-9a12-f9dfbbaf8fbe","resolution":{"observed_at":"2026-08-06T19:18:37.753788Z","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":"2026-08-06T19:18:37.855854Z","title":"QuaPy: A python-based framework for quantification","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.855854Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:254953d752287d155918634607aa6c31a880b444a538825f94d0c82fedbe2554","observation_id":"e1f48b07-00de-4ea9-b8a8-a8dec6043534","resolution":{"observed_at":"2026-08-06T19:18:37.855854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1810.04805","last_updated":"2019-05-24T20:37:26Z","snapshot_observed_at":"2026-07-30T09:12:38.100527Z","submitted_at":"2018-10-11T00:50:01Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.04805","snapshot_observed_at":"2026-08-06T19:18:37.941753Z","title":"BERT: Pre-training of deep bidirectional transformers for language understanding","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:37.941753Z"},"links":{"cited_paper":"/paper/1810.04805","citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:447002e49e82e12920e3843fe239b7e1a7630e3a35ce1d99715c28462633b639","observation_id":"4caadce5-b264-49bc-9348-1cba638d69ea","resolution":{"observed_at":"2026-08-06T19:18:37.941753Z","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":"10.24963/ijcai.2020/366","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:40.155964Z","title":"The importance of the test set size in quantification assessment","venue":null,"work_id":"8a08e9d4-57a9-48e0-ba1b-7cd6a5bdbc78","year":2020},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.067673Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:0631cde0c7b7a0d36af9ddd2b0fe41976ce5e207c255a3dd80fff7e431e04275","observation_id":"9cf99a40-71bf-4065-bdcc-b1c46c1db30a","resolution":{"observed_at":"2026-08-06T19:18:40.281951Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"document/5694031","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:42.808757Z","title":"Quan- tification via probability estimators","venue":null,"work_id":"61ed6ec0-cfab-4d33-b7aa-43f8f9573451","year":2010},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.165081Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:128a9bbcdf3c44207a6664de0d55bf071f5817011691a0bed5099f1913020af8","observation_id":"e612b9d8-17c5-45f1-9bd4-9b243ce9f8c2","resolution":{"observed_at":"2026-08-06T19:18:42.892135Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-642-13022-9_29","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:03:56.115653Z","title":"Guzmán- Martínez, and Enrique Alegre","venue":"Lecture notes in computer science","work_id":"b0ce9720-fa26-4c16-a08d-8fe4a418de61","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.232233Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:58e9cad025f2fe6f43c972306c8adf4618af4c5665dbc66ac231982ef6a75445","observation_id":"bde34629-426c-4b8d-b966-6e03251644ec","resolution":{"observed_at":"2026-08-06T19:18:40.021314Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:38.297343Z","title":"Adjusting the outputs of a classifier to new a priori probabilities: A simple procedure","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.297343Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:2cc5327c8fec50144a82afee45699024a65f6ae5dbf492ecc3df56bcf4de653c","observation_id":"8d725617-efa3-431e-81eb-9644504b1a30","resolution":{"observed_at":"2026-08-06T19:18:38.297343Z","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":"10.1145/3433164","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:39.705512Z","title":"A critical reassessment of the saerens- latinne-decaestecker algorithm for posterior probability adjustment","venue":null,"work_id":"79879df0-0429-432f-a792-cb5cb118df15","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.402188Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:64a813fd31dd6540b184f2d79dc2a3753f08e904bc8a3cf7cff2d62c7b3e4fb7","observation_id":"fa767fca-0b65-4e42-b781-8a96e117dc99","resolution":{"observed_at":"2026-08-06T19:18:39.797529Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:44.317480Z","title":"Maximum likelihood with bias- corrected calibration is hard-to-beat at label shift adaptation","venue":null,"work_id":"d41e46bf-6aa7-4124-96ef-11cdfc649418","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.502805Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:0dc0092dfa194c49dfb71b3300fdbd9a84875391126d7ce43f5c8d5c577fa376","observation_id":"b23e5a19-e841-457f-be33-1dd7467cc428","resolution":{"observed_at":"2026-08-06T19:18:44.433070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.08209","last_updated":"2021-09-22T15:57:40Z","snapshot_observed_at":"2026-07-06T11:29:56.695924Z","submitted_at":"2021-07-17T09:28:06Z","title":"Minimising quantifier variance under prior probability shift","version":4},"cited_work":{"arxiv_id":"2107.08209","doi":null,"metadata_source":"pith","pith_arxiv_id":"2107.08209","snapshot_observed_at":"2026-08-06T19:18:42.528743Z","title":"Minimising quantifier variance under prior probability shift","venue":"stat.ML","work_id":"1547e108-1799-489c-9523-2a10542793db","year":2021},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.634483Z"},"links":{"cited_paper":"/paper/2107.08209","citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:59e7b749ea53d71c1c47deec4438c40e286faefd60a46b1a1d0b4dba435f35a7","observation_id":"6e480561-d366-4eea-b873-5b71d154054d","resolution":{"observed_at":"2026-08-06T19:18:42.643587Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.patcog.2014.07.032","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:39.492100Z","title":"Quantification-oriented learning based on reliable classifiers","venue":null,"work_id":"c8e75c56-ead8-4f42-934a-00426c32e975","year":2014},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.760586Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:a7901a2cb2ca3a341ad70709a441ff9e14d085fbea285531cb88927055043f55","observation_id":"0a2055dd-a2fe-4fea-9287-f3e0f029419b","resolution":{"observed_at":"2026-08-06T19:18:39.586997Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.03223","last_updated":"2025-03-04T15:20:55Z","snapshot_observed_at":"2026-07-06T10:46:57.608963Z","submitted_at":"2021-03-04T18:51:06Z","title":"A Comparative Evaluation of Quantification Methods","version":5},"cited_work":{"arxiv_id":"2103.03223","doi":null,"metadata_source":"pith","pith_arxiv_id":"2103.03223","snapshot_observed_at":"2026-08-06T19:18:42.263837Z","title":"A Comparative Evaluation of Quantification Methods","venue":"cs.LG","work_id":"353af87c-4441-4097-befe-46cba55ddf87","year":2021},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.809672Z"},"links":{"cited_paper":"/paper/2103.03223","citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:316b24fd957bac29c0dc7f3eba00544ca6444a2e80e3ac04de91d568778266c5","observation_id":"7860acd7-49ca-49b5-a7d8-5591c832b151","resolution":{"observed_at":"2026-08-06T19:18:42.416341Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:43.959325Z","title":"Quantification under prior probability shift: the ratio estimator and its extensions","venue":null,"work_id":"67f5739b-25c3-4a6e-929a-06f9a3ee11c2","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.884460Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:3fb38a25171a582c587a4be7d851d054794b455e06f23450603d1f11e0d66244","observation_id":"cdd0fc84-a299-41f2-bb75-dfb46d96e006","resolution":{"observed_at":"2026-08-06T19:18:44.108914Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"document/1045786","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T19:18:42.147872Z","title":null,"venue":null,"work_id":"9a5fee88-6d03-4fa2-b552-7a49a4bd368b","year":2024},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:39.025710Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:b27fe8d80e1e239a6184e5f5216d5e07097cdd6234e7cb3a15b749f5a7bdb17f","observation_id":"00113b7c-43a8-4575-89e9-ae1c256850bb","resolution":{"observed_at":"2026-08-06T19:18:42.205187Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:39.124306Z","title":null,"venue":null,"work_id":null,"year":1977},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:39.124306Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:02d1b90f237eb768fe7f710b456a03e81e1b6f63d38cf50f7196592a4ac4e1c2","observation_id":"92b1b437-a058-4a3d-bb8e-f8bda209c7d0","resolution":{"observed_at":"2026-08-06T19:18:39.124306Z","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":"2026-08-06T19:18:43.750722Z","title":"Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods","venue":null,"work_id":"1111b96f-de1c-4834-8826-1e17fd7a7cab","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:39.229688Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:8d32736de2599ef3fee2c82bb805f4556e8f5c8d6e5ad2a3288a26a7612cecad","observation_id":"37868674-2e63-41c1-bb4e-f50f4af1aeb6","resolution":{"observed_at":"2026-08-06T19:18:43.837554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:43.495264Z","title":"That is, TPR and FPR are the same for the validation set and the test set","venue":null,"work_id":"7aa83a7f-8d15-4f42-8d59-833442bb59a7","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:39.310819Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:40e60cb089c86e30f842132d54c23f976e18011f079396493270641484bd8872","observation_id":"7f7ead77-4e7d-4350-aec3-2846c20203d4","resolution":{"observed_at":"2026-08-06T19:18:43.627678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T19:18:43.268922Z","title":"class 1 prevalence in our case) in the validation data","venue":null,"work_id":"bebf078f-a1c4-4869-84f0-ed9150c78fa4","year":null},"citing_paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:39.364955Z"},"links":{"citing_paper":"/paper/2507.06061"},"observation_digest":"sha256:488742f7ee052590c74e1d5ea55c09e3a5d475eb9458e5ca44d61d720271037d","observation_id":"bb88520b-8cb9-4451-bde7-1b4562c5016f","resolution":{"observed_at":"2026-08-06T19:18:43.323066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.06061","last_updated":"2025-07-08T15:06:02Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-06T19:09:34.370546Z","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy"},"reference_resolution":{"displayed":30,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":13,"verified_fuzzy":7},"total_outbound_references":30},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2507.06061."}