{"as_of":"2026-08-09T21:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:76bf13213dbb035fcd07884f3f88016ff649971f3899bc1ca11ad55d7aa0101e","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":"2026-08-09T06:31:02.800959+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":"2026-08-06T23:27:58.656304Z","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":"2026-08-06T23:27:59.271315Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.04874","last_updated":"2024-01-25T13:04:27Z","snapshot_observed_at":"2026-08-09T00:44:10.155186Z","submitted_at":"2024-01-25T13:04:27Z","title":"Choosing a Classical Planner with Graph Neural Networks","version":1},"cited_work":{"arxiv_id":"2402.04874","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.04874","snapshot_observed_at":"2026-08-06T23:27:59.271315Z","title":"Choosing a Classical Planner with Graph Neural Networks","venue":"cs.AI","work_id":"8e91633d-ee5a-40ad-8535-1e26e31bdec5","year":2024},"citing_paper":{"arxiv_id":"2506.17894","last_updated":"2025-06-22T04:13:30Z","snapshot_observed_at":"2026-08-07T22:24:27.768075Z","submitted_at":"2025-06-22T04:13:30Z","title":"TROJAN-GUARD: Hardware Trojans Detection Using GNN in RTL Designs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T23:27:58.656304Z"},"links":{"cited_paper":"/paper/2402.04874","citing_paper":"/paper/2506.17894"},"observation_digest":"sha256:5c8c6f791718755efddfaa326503c8e8bf5f3d9715d97c6da13b941680e616b1","observation_id":"e34af92f-f4ec-4359-a59f-4cb5b5343475","resolution":{"observed_at":"2026-08-06T23:27:59.312956Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2402.04874/citation-record","integrity":"/paper/2402.04874/integrity","json":"/paper/2402.04874/citation-record.json","paper":"/paper/2402.04874"},"outbound":[],"paper":{"arxiv_id":"2402.04874","last_updated":"2024-01-25T13:04:27Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-09T00:44:10.155186Z","submitted_at":"2024-01-25T13:04:27Z","title":"Choosing a Classical Planner with Graph Neural Networks"},"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 1 inbound Pith citation observation for arXiv:2402.04874."}