{"as_of":"2026-08-09T22:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f5f45c9eff35b845de24199267584e41b65c06cf3fa1f16776ba6708f33bb684","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-31T10:23:29.780998Z","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":"2304.12573","last_updated":"2023-04-25T04:56:35Z","snapshot_observed_at":"2026-07-31T18:44:12.831198Z","submitted_at":"2023-04-25T04:56:35Z","title":"Fairness and Bias in Truth Discovery Algorithms: An Experimental Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12573","snapshot_observed_at":"2026-07-15T12:59:04.484292Z","title":"Fairness and bias in truth discovery algorithms: An experimental analysis.arXiv preprint arXiv:2304.12573,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.13356","last_updated":"2026-07-14T13:24:15Z","snapshot_observed_at":"2026-08-08T07:22:43.777479Z","submitted_at":"2026-03-09T01:35:37Z","title":"Learning When to Trust in Contextual Social Bandits","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-15T12:59:04.484292Z"},"links":{"cited_paper":"/paper/2304.12573","citing_paper":"/paper/2603.13356"},"observation_digest":"sha256:fb246ec6f23a9c863e94f99bcb7aeefa495590429601d86b4aa4f1fccba18a81","observation_id":"af9cc9f0-4faa-4402-90e9-4a5b49d5fb5f","resolution":{"observed_at":"2026-07-15T12:59:04.484292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.12573","last_updated":"2023-04-25T04:56:35Z","snapshot_observed_at":"2026-07-31T18:44:12.831198Z","submitted_at":"2023-04-25T04:56:35Z","title":"Fairness and Bias in Truth Discovery Algorithms: An Experimental Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12573","snapshot_observed_at":"2026-07-31T10:23:29.780998Z","title":"Preprint arXiv:2304.12573 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.24622","last_updated":"2026-07-27T16:17:34Z","snapshot_observed_at":"2026-08-09T09:51:06.376497Z","submitted_at":"2026-07-27T16:17:34Z","title":"A Model for Imbalanced Label Aggregation: A Focus on Minority-Class Detection","version":1},"reference_index":119,"source":"arxiv_source","source_observed_at":"2026-07-31T10:23:29.780998Z"},"links":{"cited_paper":"/paper/2304.12573","citing_paper":"/paper/2607.24622"},"observation_digest":"sha256:875f891910217d3b4aeaf4edcad29985f67571f264661fc98ca0d323d04ca0ca","observation_id":"68123824-07b3-4d26-8bb4-b4fd4f417552","resolution":{"observed_at":"2026-07-31T10:23:29.780998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2304.12573/citation-record","integrity":"/paper/2304.12573/integrity","json":"/paper/2304.12573/citation-record.json","paper":"/paper/2304.12573"},"outbound":[],"paper":{"arxiv_id":"2304.12573","last_updated":"2023-04-25T04:56:35Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-31T18:44:12.831198Z","submitted_at":"2023-04-25T04:56:35Z","title":"Fairness and Bias in Truth Discovery Algorithms: An Experimental Analysis"},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2304.12573."}