{"as_of":"2026-08-20T01:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a373069ef06d4babf93e9f0a2fbce3a5071064cc293e16319f8124d3174f7847","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":"2026-08-19T06:32:44.657259+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":"2026-08-11T21:15:12.735587Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T15:17:39.831872Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.02618","last_updated":"2024-10-03T15:56:03Z","snapshot_observed_at":"2026-08-17T18:45:54.644623Z","submitted_at":"2024-10-03T15:56:03Z","title":"Achieving Fairness in Predictive Process Analytics via Adversarial Learning (Extended Version)","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02618","snapshot_observed_at":"2026-08-11T21:15:12.735587Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.04914","last_updated":"2025-04-28T13:03:01Z","snapshot_observed_at":"2026-08-20T01:49:33.545851Z","submitted_at":"2024-12-06T10:10:47Z","title":"Achieving Group Fairness through Independence in Predictive Process Monitoring","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T21:15:12.735587Z"},"links":{"cited_paper":"/paper/2410.02618","citing_paper":"/paper/2412.04914"},"observation_digest":"sha256:8b361426cb57050f9c34af60047512efa2c80a7dc369c3dd508574129a33d9e5","observation_id":"c11be0e7-cb1d-4ddf-8ff7-1e89941e7ae0","resolution":{"observed_at":"2026-08-11T21:15:12.735587Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02618","last_updated":"2024-10-03T15:56:03Z","snapshot_observed_at":"2026-08-17T18:45:54.644623Z","submitted_at":"2024-10-03T15:56:03Z","title":"Achieving Fairness in Predictive Process Analytics via Adversarial Learning (Extended Version)","version":1},"cited_work":{"arxiv_id":"2410.02618","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.02618","snapshot_observed_at":"2026-08-05T15:17:39.831872Z","title":"Achieving Fairness in Predictive Process Analytics via Adversarial Learning (Extended Version)","venue":"cs.AI","work_id":"7ec7f6b1-c7b6-446d-82a0-7eedd56994ba","year":2024},"citing_paper":{"arxiv_id":"2508.20021","last_updated":"2025-08-27T16:30:30Z","snapshot_observed_at":"2026-08-18T01:21:28.361388Z","submitted_at":"2025-08-27T16:30:30Z","title":"FairLoop: Software Support for Human-Centric Fairness in Predictive Business Process Monitoring","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T15:17:39.789444Z"},"links":{"cited_paper":"/paper/2410.02618","citing_paper":"/paper/2508.20021"},"observation_digest":"sha256:b784cbb113d5aed8162371fd6c57a8b52149fcb87af45711b0b69e7551fe49e5","observation_id":"8e62cbc7-7432-4b52-926d-637b8de8b4fa","resolution":{"observed_at":"2026-08-05T15:17:39.839983Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2410.02618/citation-record","integrity":"/paper/2410.02618/integrity","json":"/paper/2410.02618/citation-record.json","paper":"/paper/2410.02618"},"outbound":[],"paper":{"arxiv_id":"2410.02618","last_updated":"2024-10-03T15:56:03Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-17T18:45:54.644623Z","submitted_at":"2024-10-03T15:56:03Z","title":"Achieving Fairness in Predictive Process Analytics via Adversarial Learning (Extended Version)"},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.02618."}