{"as_of":"2026-08-13T18:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:baf7a1b2884e94182ce666fe00ea7d5dabb61f2e09ed434f99ba984b7f6dd4e1","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":"2026-08-13T06:32:02.005865+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":"2026-08-12T13:05:05.040295Z","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":"2026-07-11T08:37:53.985384Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.01034","last_updated":"2025-04-15T11:30:51Z","snapshot_observed_at":"2026-08-13T10:34:17.464080Z","submitted_at":"2024-10-01T19:50:18Z","title":"Finding radio transients with anomaly detection and active learning based on volunteer classifications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01034","snapshot_observed_at":"2026-08-12T13:05:05.040295Z","title":"2024, arXiv e-prints, arXiv:2410.01034, 10.48550/arXiv.2410.01034","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.16556","last_updated":"2025-06-24T18:10:40Z","snapshot_observed_at":"2026-08-12T12:56:46.613740Z","submitted_at":"2024-11-25T16:40:19Z","title":"Anomaly Detection and Radio-frequency Interference Classification with Unsupervised Learning in Narrowband Radio Technosignature Searches","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-12T13:05:05.040295Z"},"links":{"cited_paper":"/paper/2410.01034","citing_paper":"/paper/2411.16556"},"observation_digest":"sha256:d0eace64ac7c9003e9a64a63f9428e80418ff0566123802b22c7d868579309de","observation_id":"85767d9f-5d56-4387-96ba-e65f77c4e268","resolution":{"observed_at":"2026-08-12T13:05:05.040295Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01034","last_updated":"2025-04-15T11:30:51Z","snapshot_observed_at":"2026-08-13T10:34:17.464080Z","submitted_at":"2024-10-01T19:50:18Z","title":"Finding radio transients with anomaly detection and active learning based on volunteer classifications","version":2},"cited_work":{"arxiv_id":"2410.01034","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.01034","snapshot_observed_at":"2026-07-11T08:37:53.985384Z","title":"Finding radio transients with anomaly detection and active learning based on volunteer classifications","venue":"astro-ph.IM","work_id":"e3e9f915-0199-4cab-b901-8be61647a92f","year":2024},"citing_paper":{"arxiv_id":"2607.05118","last_updated":"2026-07-06T14:06:34Z","snapshot_observed_at":"2026-08-08T13:37:36.329111Z","submitted_at":"2026-07-06T14:06:34Z","title":"Commensal image plane transient search methods with the SKAO","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-07-11T08:33:18.894541Z"},"links":{"cited_paper":"/paper/2410.01034","citing_paper":"/paper/2607.05118"},"observation_digest":"sha256:f04809952ef2f845eb5ab5909fff64208723c3d1f26d7db89e51daee647a29de","observation_id":"22d6cf4b-8f98-4e4f-8324-935cca75d349","resolution":{"observed_at":"2026-07-11T08:37:53.987627Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2410.01034/citation-record","integrity":"/paper/2410.01034/integrity","json":"/paper/2410.01034/citation-record.json","paper":"/paper/2410.01034"},"outbound":[],"paper":{"arxiv_id":"2410.01034","last_updated":"2025-04-15T11:30:51Z","latest_version":2,"primary_category":"astro-ph.IM","snapshot_observed_at":"2026-08-13T10:34:17.464080Z","submitted_at":"2024-10-01T19:50:18Z","title":"Finding radio transients with anomaly detection and active learning based on volunteer classifications"},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.01034."}