{"as_of":"2026-08-18T20:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3a350453286dac16ff30140ea0d75484b20b91b7594b033130d28cadac1b9d15","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":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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":"2026-08-16T10:48:20.945345Z","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":"2026-08-16T10:48:21.874550Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.02696","last_updated":"2024-02-05T03:20:28Z","snapshot_observed_at":"2026-08-18T18:49:48.981928Z","submitted_at":"2024-02-05T03:20:28Z","title":"Causal Feature Selection for Responsible Machine Learning","version":1},"cited_work":{"arxiv_id":"2402.02696","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.02696","snapshot_observed_at":"2026-08-16T10:48:21.874550Z","title":"Causal Feature Selection for Responsible Machine Learning","venue":"cs.LG","work_id":"8278f54a-b8fb-4e2d-b17d-08c600caae33","year":2024},"citing_paper":{"arxiv_id":"2504.17356","last_updated":"2026-07-20T03:05:41Z","snapshot_observed_at":"2026-08-17T13:05:13.180965Z","submitted_at":"2025-04-24T08:16:36Z","title":"Comprehend, Divide, and Conquer: Feature Subspace Exploration via Multi-Agent Hierarchical Reinforcement Learning","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T10:48:20.945345Z"},"links":{"cited_paper":"/paper/2402.02696","citing_paper":"/paper/2504.17356"},"observation_digest":"sha256:99fc0a142a824885b7a0432799752ec8579fe98986ff8d7df09f7baf66e289b6","observation_id":"0aa76399-100b-46ed-99a9-ec72e40606f9","resolution":{"observed_at":"2026-08-16T10:48:21.996561Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.02696/citation-record","integrity":"/paper/2402.02696/integrity","json":"/paper/2402.02696/citation-record.json","paper":"/paper/2402.02696"},"outbound":[],"paper":{"arxiv_id":"2402.02696","last_updated":"2024-02-05T03:20:28Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T18:49:48.981928Z","submitted_at":"2024-02-05T03:20:28Z","title":"Causal Feature Selection for Responsible Machine Learning"},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2402.02696."}