{"as_of":"2026-08-19T17:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0175c55b3dc88d81b59c2e3d2fdc68de4ab81ed273b89a01f65294f9ef906da8","coverage":[{"denominator":27,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":27,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T10:24:04.868995Z","state":"measured"},{"denominator":27,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":27,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/2504.18262/citation-record","integrity":"/paper/2504.18262/integrity","json":"/paper/2504.18262/citation-record.json","paper":"/paper/2504.18262"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:05.596608Z","title":"Learning optimal and fair decision trees for non-discriminative decision-making","venue":null,"work_id":"664a2611-8f13-43db-945e-f8d13155ef5c","year":2019},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.704580Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:81ea220de8a6c560859079c218e8f98bff7438186b6972270361b2a690a9a255","observation_id":"5332c598-e9c7-4198-9b7e-404c582cd108","resolution":{"observed_at":"2026-08-16T10:24:05.602227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.570263Z","title":"Machine bias","venue":null,"work_id":"85aeece2-8bba-4ae3-b700-9c6338f45f8e","year":2016},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.712014Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:23ad7f99e84adcfc70f40124c24ad8b46e5e2c847f3b223817ce7c087e23e829","observation_id":"91db1808-13a1-4d6a-a405-94f2827ea4f4","resolution":{"observed_at":"2026-08-16T10:24:05.576824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.549276Z","title":"Fairness and Machine Learning","venue":null,"work_id":"24a823ea-e0ac-4934-968c-001b0a71d8bf","year":2019},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.718162Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:8be1bcd7de6fcc55136af4f33888e5bc4f3562dc4b93973a477e6dcccce56fc0","observation_id":"7d88a4dc-d0ea-4e59-9309-be2df12b919e","resolution":{"observed_at":"2026-08-16T10:24:05.554991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.530286Z","title":null,"venue":null,"work_id":"36a76081-107b-4d76-af35-af7c806ba42c","year":2017},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.723906Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:d159fbfe22d6f3fb5837bfc5351854c9dac27e51cc03248d9ceafd9d719b8bfc","observation_id":"aaa86b67-1183-434c-be5e-3bb67657ae09","resolution":{"observed_at":"2026-08-16T10:24:05.535700Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.508094Z","title":"Fairness constraints: A flexible approach for fair classification","venue":null,"work_id":"2a2b894a-c5e9-499e-8549-24ae937a1615","year":2019},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.730541Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:b93a54bf3f422c2ac6cb4e28b1396c5f0c4f316a3e8702c09a81773aecddf408","observation_id":"05d38bfd-d026-4f76-857e-e075de16187f","resolution":{"observed_at":"2026-08-16T10:24:05.515463Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.483109Z","title":"Classification and Regression Trees","venue":null,"work_id":"e6abba04-c5d3-4dbe-bdeb-71f7c2f98cf5","year":1984},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.736471Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:b87e191e0104f1c92bef09af14ace24669f2e1743eddcad6f1be2b9224fc48fe","observation_id":"4154f5c7-1c83-42b7-9fe6-2d5a8bd52842","resolution":{"observed_at":"2026-08-16T10:24:05.492111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:04.743795Z","title":"Fairness through awareness","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.743795Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:4993e02465807c203784dac7980ab3cd37dd52c1f7a46bb21f19cfd6ec172fc2","observation_id":"79d02d5b-3187-4cf7-b99e-1ee0d4896e2c","resolution":{"observed_at":"2026-08-16T10:24:04.743795Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.00250","last_updated":"2020-04-02T15:18:18Z","snapshot_observed_at":"2026-08-18T01:42:15.474982Z","submitted_at":"2019-06-01T16:09:23Z","title":"Metric Learning for Individual Fairness","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.00250","snapshot_observed_at":"2026-08-16T10:24:04.748977Z","title":"Metric learning for individual fairness","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.748977Z"},"links":{"cited_paper":"/paper/1906.00250","citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:a2649026648c232ac7b70014015ecfe7f0462ce4567984d0cc4cbc6aa5a02e4c","observation_id":"6f4c4916-4910-47f9-bf38-7141a3722784","resolution":{"observed_at":"2026-08-16T10:24:04.748977Z","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":"2026-08-16T10:24:05.458546Z","title":"An algo- rithm for removing sensitive information: Applica- tion to race-independent recidivism prediction","venue":null,"work_id":"a2dc5760-f2b3-4503-8e88-6a1c01468198","year":2019},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.756175Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:0d4d5bf0658be659e6dff52190d0ae2268d04c89390f5931ebedcf60ff1d2233","observation_id":"4579b326-f44a-4795-a4d6-5478e1123ab2","resolution":{"observed_at":"2026-08-16T10:24:05.464762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:04.768847Z","title":"Discrimination aware decision tree learn- ing","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.768847Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:344e377c8b7326e3e0bea89f9b962a461c288a54baeac171077f2bc887bbfa47","observation_id":"71e52cd9-5cc5-4579-89ab-51ade8705f2f","resolution":{"observed_at":"2026-08-16T10:24:04.768847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1703.06856","last_updated":"2018-03-08T11:23:13Z","snapshot_observed_at":"2026-08-14T21:10:57.213409Z","submitted_at":"2017-03-20T17:18:57Z","title":"Counterfactual Fairness","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.06856","snapshot_observed_at":"2026-08-16T10:24:04.777937Z","title":"Counterfactual fairness","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.777937Z"},"links":{"cited_paper":"/paper/1703.06856","citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:f144e6bdc6a59d8f28e7b13b67bf8060ce65e7ad44ad01fffc4eef615bd72405","observation_id":"eca9af70-1be0-4c21-b9f2-16cba3d4e07d","resolution":{"observed_at":"2026-08-16T10:24:04.777937Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.00530","last_updated":"2022-01-21T13:00:50Z","snapshot_observed_at":"2026-08-16T17:52:26.797856Z","submitted_at":"2021-10-01T16:54:04Z","title":"A survey on datasets for fairness-aware machine learning","version":3},"cited_work":{"arxiv_id":"2110.00530","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.00530","snapshot_observed_at":"2026-08-16T10:24:05.019015Z","title":"A survey on datasets for fairness-aware machine learning","venue":"cs.LG","work_id":"86403b1a-6cc7-42bd-8579-01de0836e24b","year":2021},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.786262Z"},"links":{"cited_paper":"/paper/2110.00530","citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:646fc0685fc882f13dc6113c5976b162ffdef817fdf53eb876f349594d0bf0b7","observation_id":"189dc7d4-0cee-4a21-9fe5-a5b9680af36f","resolution":{"observed_at":"2026-08-16T10:24:05.024572Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.09635","last_updated":"2022-01-25T05:42:50Z","snapshot_observed_at":"2026-08-18T03:47:09.917267Z","submitted_at":"2019-08-23T01:22:04Z","title":"A Survey on Bias and Fairness in Machine Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.09635","snapshot_observed_at":"2026-08-16T10:24:04.792766Z","title":"A Survey on Bias and Fair- ness in Machine Learning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.792766Z"},"links":{"cited_paper":"/paper/1908.09635","citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:17d88f7313ed0d22ec4f33199e689d6a648466620da8a74782a0fb8b79daec30","observation_id":"83dbd92e-4647-489b-be57-320fbafd2eea","resolution":{"observed_at":"2026-08-16T10:24:04.792766Z","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":"2026-08-16T10:24:05.438003Z","title":"Algorithmic fairness: Choices, assumptions, and definitions","venue":null,"work_id":"c58d26cb-55e7-4399-a2c3-697301ae6bad","year":2021},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.801924Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:070f943d9e06a58d4169df8c534e0c445b2d35fad30ae9c223f5893532b813ba","observation_id":"4a5c8eb0-b719-4782-b08f-f8876de8feed","resolution":{"observed_at":"2026-08-16T10:24:05.443641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.393430Z","title":"deste- fano","venue":null,"work_id":"cc7e9965-4889-4ced-9544-5ae4444ef5ae","year":2009},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.813335Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:8bec4b24b4b189286b2c37624ed7c15f34b4046dda6f73a98ad1f2472f2d0baf","observation_id":"4b5d8bbd-13b9-4a98-9dfa-21f8e07b1983","resolution":{"observed_at":"2026-08-16T10:24:05.400273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.349329Z","title":"Pattern Recogonition and Neural Net- works","venue":null,"work_id":"bbd6e4a3-f6d3-4e65-ad71-07b8b309e482","year":2005},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.824152Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:79a496c42d99f2573fe9c195c791a71ce15ee6cd8366567d050724793392abca","observation_id":"8330f628-f3b7-480f-87f4-574adbfb4fa3","resolution":{"observed_at":"2026-08-16T10:24:05.356604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.323738Z","title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead","venue":null,"work_id":"45576789-d667-4d53-9ef4-819422a7205b","year":2019},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.829125Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:c6e458bf577c539bcdb95545b52085f92df9818b2e504b78798aedbb921e5efb","observation_id":"dc1d5ea1-1a01-4cde-b177-de6b5585c524","resolution":{"observed_at":"2026-08-16T10:24:05.329982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.16785","last_updated":"2021-03-31T03:06:57Z","snapshot_observed_at":"2026-08-19T14:51:38.861440Z","submitted_at":"2021-03-31T03:06:57Z","title":"Individually Fair Gradient Boosting","version":1},"cited_work":{"arxiv_id":"2103.16785","doi":null,"metadata_source":"pith","pith_arxiv_id":"2103.16785","snapshot_observed_at":"2026-08-16T10:24:04.962473Z","title":"Individually Fair Gradient Boosting","venue":"cs.LG","work_id":"be961a1c-1ab6-460c-9844-fddbbacf6e5c","year":2021},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.834501Z"},"links":{"cited_paper":"/paper/2103.16785","citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:b3d204e459a097d54e36a905dac05bd2bc5b86204a57116ae5698be494cff613","observation_id":"3d210e28-6104-4376-862e-acf1417c6fc5","resolution":{"observed_at":"2026-08-16T10:24:04.970504Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.304371Z","title":"Fairness definitions explained","venue":null,"work_id":"4dd76493-0559-4d11-b70c-a8ccd3e07c50","year":2018},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.839856Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:dc01df5e65b7ed6d3dd786f2e7066b36caeb08c3abed14f0c42c3ac1c93121a2","observation_id":"9e36fc1f-4a75-4a4b-b1db-65252fe7e71b","resolution":{"observed_at":"2026-08-16T10:24:05.309828Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.284682Z","title":"LSAC National Longitudinal Bar Passage Study. LSAC Research Report Series","venue":null,"work_id":"e9e8e3e4-76b1-467d-b5d0-c962bad49e57","year":1998},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.844767Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:0711747f457994451eb87df3c341eb21c8daad1d1412e6049f6ca76ca8262a95","observation_id":"c01e9cde-5b73-4a4b-a5c3-19aef2fdb192","resolution":{"observed_at":"2026-08-16T10:24:05.291155Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.263166Z","title":"Trustworthy ai","venue":null,"work_id":"e768da8b-f731-4c89-b2f3-685c17ed9efe","year":2021},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.850043Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:af0c3c562ff81ac7aa8bc9c2632d5a7c728df94062a06bc5cf779e07b412fb2c","observation_id":"855cf0ed-7011-4156-bf85-8774d15fd96e","resolution":{"observed_at":"2026-08-16T10:24:05.269088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.244129Z","title":"Numerical op- timization","venue":null,"work_id":"88411df6-19c6-4bc0-8d9e-979611b3c485","year":1999},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.856154Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:730f2464e5856a8798ea25634f13eb18553a582ad897d70041424bf6adee4516","observation_id":"0998f0de-094a-418e-bd3e-b97469590e38","resolution":{"observed_at":"2026-08-16T10:24:05.249888Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+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":"2026-08-16T10:24:05.221900Z","title":"Training individually fair ML models with Sensitive Subspace Robustness","venue":null,"work_id":"b40c26fe-e78e-4804-99f6-c0309d026b7d","year":2019},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.862172Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:52d17124b61b5d87f7fb3687bbd69b17ee3b8d9a224a99d3ca7bdcf9fbca27d7","observation_id":"eed2aad4-b7e2-4683-90d4-8aee8095042e","resolution":{"observed_at":"2026-08-16T10:24:05.228012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.00020","last_updated":"2020-03-13T05:25:24Z","snapshot_observed_at":"2026-08-19T13:27:59.122081Z","submitted_at":"2019-06-28T18:11:25Z","title":"Training individually fair ML models with Sensitive Subspace Robustness","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.00020","snapshot_observed_at":"2026-08-16T10:24:04.868995Z","title":"url: http://arxiv.org/ abs/1907.00020","venue":null,"work_id":null,"year":1907},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.868995Z"},"links":{"cited_paper":"/paper/1907.00020","citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:57f6e87410c11456e3ab110f2e5d50c4f012a3b39ca82d5937e8acfb69dcdb2e","observation_id":"a5319e8e-840d-4f44-b0d1-f23ebe0f3c15","resolution":{"observed_at":"2026-08-16T10:24:04.868995Z","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":"2026-08-16T10:24:05.419700Z","title":null,"venue":null,"work_id":"58650c07-f3f5-47af-bc26-72f2b4aa713c","year":null},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":163,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.807619Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:ca216b772edf33658b0b4d98cf40cd4b37105179c1eb4a0667d627ac3a2e1d85","observation_id":"990366db-eb20-490c-97aa-1246e2ed3073","resolution":{"observed_at":"2026-08-16T10:24:05.425780Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.04957","last_updated":"2017-03-15T06:36:58Z","snapshot_observed_at":"2026-08-14T21:11:52.075048Z","submitted_at":"2017-03-15T06:36:58Z","title":"An algorithm for removing sensitive information: application to race-independent recidivism prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.04957","snapshot_observed_at":"2026-08-16T10:24:04.761830Z","title":"doi: 10.1214/18- AOAS1201","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":220,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.761830Z"},"links":{"cited_paper":"/paper/1703.04957","citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:20dd3babb2c906d3c3c44ad4520dd63232658a88f95c3efaa7e84229a009418f","observation_id":"cb3bb586-7dd1-4121-8ece-249b12fc805c","resolution":{"observed_at":"2026-08-16T10:24:04.761830Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:24:05.370798Z","title":null,"venue":null,"work_id":"b3d0a7b9-63ac-46cc-8600-27ec070d4af5","year":null},"citing_paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees","version":1},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-16T10:24:04.818594Z"},"links":{"citing_paper":"/paper/2504.18262"},"observation_digest":"sha256:da956f849b55ed3c136ff83f9a7b5c8abe8907207081f267917cf4171a4b74e7","observation_id":"01656001-5739-442b-a241-7a2086245440","resolution":{"observed_at":"2026-08-16T10:24:05.377117Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.18262","last_updated":"2025-04-25T11:15:55Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-19T05:25:44.643887Z","submitted_at":"2025-04-25T11:15:55Z","title":"Local Statistical Parity for the Estimation of Fair Decision Trees"},"reference_resolution":{"displayed":27,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":2,"verified_fuzzy":15},"total_outbound_references":27},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2504.18262."}