{"as_of":"2026-08-06T05:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9da371b4decd79fa74d10393a405144c8d911b140aa8f3d86f58e5ab2b4de66c","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":"2026-08-05T06:32:48.257954+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":"2026-05-13T20:52:59.566447Z","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":"2026-05-13T20:53:15.292050Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2112.07508","last_updated":"2022-06-17T09:00:26Z","snapshot_observed_at":"2026-07-06T12:18:38.814450Z","submitted_at":"2021-12-14T16:12:30Z","title":"Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs","version":3},"cited_work":{"arxiv_id":"2112.07508","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2112.07508","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"78a932a0-aaf8-4786-bded-9dce0c7653a4","year":2022},"citing_paper":{"arxiv_id":"2604.02899","last_updated":"2026-04-03T09:14:39Z","snapshot_observed_at":"2026-08-03T17:05:55.935192Z","submitted_at":"2026-04-03T09:14:39Z","title":"Extracting Money Laundering Transactions from Quasi-Temporal Graph Representation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-13T20:52:59.566447Z"},"links":{"cited_paper":"/paper/2112.07508","citing_paper":"/paper/2604.02899"},"observation_digest":"sha256:4c86206dd6f232414cf72942a890a16feb5b8fb539ada82da9f383c117c7b1ca","observation_id":"2e51ac3e-1769-437b-b6e9-a78efeac8c38","resolution":{"observed_at":"2026-05-13T20:53:15.293624Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.07508","last_updated":"2022-06-17T09:00:26Z","snapshot_observed_at":"2026-07-06T12:18:38.814450Z","submitted_at":"2021-12-14T16:12:30Z","title":"Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs","version":3},"cited_work":{"arxiv_id":"2112.07508","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2112.07508","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"78a932a0-aaf8-4786-bded-9dce0c7653a4","year":2022},"citing_paper":{"arxiv_id":"2604.12241","last_updated":"2026-04-14T03:34:44Z","snapshot_observed_at":"2026-08-02T16:01:51.018604Z","submitted_at":"2026-04-14T03:34:44Z","title":"BlazingAML: High-Throughput Anti-Money Laundering (AML) via Multi-Stage Graph Mining","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T16:02:06.747576Z"},"links":{"cited_paper":"/paper/2112.07508","citing_paper":"/paper/2604.12241"},"observation_digest":"sha256:926bdc750a66ea2dcde93a31720f5ddbb4a6c085ff28aea3f810b13d89643111","observation_id":"9ff2b4ac-060d-4f85-97f7-1e5f90f8a8fd","resolution":{"observed_at":"2026-05-11T09:26:01.257746Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2112.07508/citation-record","integrity":"/paper/2112.07508/integrity","json":"/paper/2112.07508/citation-record.json","paper":"/paper/2112.07508"},"outbound":[],"paper":{"arxiv_id":"2112.07508","last_updated":"2022-06-17T09:00:26Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T12:18:38.814450Z","submitted_at":"2021-12-14T16:12:30Z","title":"Anti-Money Laundering Alert Optimization Using Machine Learning with Graphs"},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2112.07508."}