{"as_of":"2026-08-08T11:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:bfc51e504ddd71fc3961eb7b771b94a34d4f6624fb5bdf180c08786f6c75ded8","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:52:36.334992Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-29T10:03:17.050519Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2010.09553","last_updated":"2022-06-07T17:38:12Z","snapshot_observed_at":"2026-07-06T10:05:47.267562Z","submitted_at":"2020-10-19T14:28:55Z","title":"Survey on Causal-based Machine Learning Fairness Notions","version":7},"cited_work":{"arxiv_id":"2010.09553","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2010.09553","snapshot_observed_at":"2026-06-29T10:03:17.050519Z","title":"Survey on causal-based machine learning fairness notions, 2022","venue":null,"work_id":"d1d6e7f0-31ca-45e7-933b-2ede917d6585","year":2022},"citing_paper":{"arxiv_id":"2205.08809","last_updated":"2022-05-18T09:18:08Z","snapshot_observed_at":"2026-08-02T21:52:02.092797Z","submitted_at":"2022-05-18T09:18:08Z","title":"Software Fairness: An Analysis and Survey","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-05-24T12:04:40.732437Z"},"links":{"cited_paper":"/paper/2010.09553","citing_paper":"/paper/2205.08809"},"observation_digest":"sha256:e0e1cdc6226700e6b12ac1cc9c02aae39ce61237a6c0da6878a9ad29561285fc","observation_id":"62006ae3-24be-4262-b00d-cb3acadd88f1","resolution":{"observed_at":"2026-05-24T12:06:10.972996Z","resolver_source":"arxiv_id","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":"2010.09553","last_updated":"2022-06-07T17:38:12Z","snapshot_observed_at":"2026-07-06T10:05:47.267562Z","submitted_at":"2020-10-19T14:28:55Z","title":"Survey on Causal-based Machine Learning Fairness Notions","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.09553","snapshot_observed_at":"2026-08-06T18:52:36.334992Z","title":"Survey on causal-based machine learning fairness notions,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.07026","last_updated":"2025-07-09T16:57:59Z","snapshot_observed_at":"2026-08-06T18:46:41.027759Z","submitted_at":"2025-07-09T16:57:59Z","title":"Exploring Fairness Interventions in Open Source Projects","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T18:52:36.334992Z"},"links":{"cited_paper":"/paper/2010.09553","citing_paper":"/paper/2507.07026"},"observation_digest":"sha256:105899c854e055f0097eeac9da965cad6011c84c59eac940d11519dad0f5ee18","observation_id":"f7461a03-9976-449d-a5c8-0a1061c6a40f","resolution":{"observed_at":"2026-08-06T18:52:36.334992Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.09553","last_updated":"2022-06-07T17:38:12Z","snapshot_observed_at":"2026-07-06T10:05:47.267562Z","submitted_at":"2020-10-19T14:28:55Z","title":"Survey on Causal-based Machine Learning Fairness Notions","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.09553","snapshot_observed_at":"2026-08-06T14:35:05.829399Z","title":"Survey on causal-based machine learning fairness notions","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2507.18726","last_updated":"2025-07-24T18:16:44Z","snapshot_observed_at":"2026-08-06T14:35:04.769035Z","submitted_at":"2025-07-24T18:16:44Z","title":"Exploring the Landscape of Fairness Interventions in Software Engineering","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T14:35:05.829399Z"},"links":{"cited_paper":"/paper/2010.09553","citing_paper":"/paper/2507.18726"},"observation_digest":"sha256:4ba34e43abf750c1a810b49500a04e44db11dc1cf978e076c07cf07e01bdfc2f","observation_id":"1fbaa55e-d1b8-4775-9b6f-6e342f8f7874","resolution":{"observed_at":"2026-08-06T14:35:05.829399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.09553","last_updated":"2022-06-07T17:38:12Z","snapshot_observed_at":"2026-07-06T10:05:47.267562Z","submitted_at":"2020-10-19T14:28:55Z","title":"Survey on Causal-based Machine Learning Fairness Notions","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.09553","snapshot_observed_at":"2026-08-05T23:52:57.194673Z","title":"Survey on causal-based machine learning fairness notions","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2508.08337","last_updated":"2026-05-29T19:13:54Z","snapshot_observed_at":"2026-08-05T23:00:35.599418Z","submitted_at":"2025-08-10T23:55:16Z","title":"Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants","version":3},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-05T23:52:57.194673Z"},"links":{"cited_paper":"/paper/2010.09553","citing_paper":"/paper/2508.08337"},"observation_digest":"sha256:e997dac0920a2fcf6e087239ec325b6288fdba82f0343e689b2e262442e8b86e","observation_id":"85316e35-79e1-4498-a326-a061e762cb9e","resolution":{"observed_at":"2026-08-05T23:52:57.194673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.09553","last_updated":"2022-06-07T17:38:12Z","snapshot_observed_at":"2026-07-06T10:05:47.267562Z","submitted_at":"2020-10-19T14:28:55Z","title":"Survey on Causal-based Machine Learning Fairness Notions","version":7},"cited_work":{"arxiv_id":"2010.09553","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2010.09553","snapshot_observed_at":"2026-06-29T10:03:17.050519Z","title":"Survey on causal-based machine learning fairness notions, 2022","venue":null,"work_id":"d1d6e7f0-31ca-45e7-933b-2ede917d6585","year":2022},"citing_paper":{"arxiv_id":"2605.28251","last_updated":"2026-05-27T10:00:54Z","snapshot_observed_at":"2026-07-06T23:37:50.157617Z","submitted_at":"2026-05-27T10:00:54Z","title":"Counterfactually Fair Regression via Optimal Transport","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-29T10:02:28.572006Z"},"links":{"cited_paper":"/paper/2010.09553","citing_paper":"/paper/2605.28251"},"observation_digest":"sha256:e73e2e9e45e2c73441ca98f3b45bf501e5ffc9898670cc641952552269f26263","observation_id":"cc2f43ea-dffe-4540-8cba-c5abc2e5cd10","resolution":{"observed_at":"2026-06-29T10:03:17.051923Z","resolver_source":"arxiv_id","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"}}],"links":{"evidence":"/evidence","html":"/paper/2010.09553/citation-record","integrity":"/paper/2010.09553/integrity","json":"/paper/2010.09553/citation-record.json","paper":"/paper/2010.09553"},"outbound":[],"paper":{"arxiv_id":"2010.09553","last_updated":"2022-06-07T17:38:12Z","latest_version":7,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T10:05:47.267562Z","submitted_at":"2020-10-19T14:28:55Z","title":"Survey on Causal-based Machine Learning Fairness Notions"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2010.09553."}