{"as_of":"2026-08-09T13:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:165c629cf6a7e6c0ddde301cd77e0d9ec269df37a1a5a819066b88bdac49ec31","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":"2026-08-04T07:43:30.780775Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.15297","last_updated":"2025-02-24T07:30:05Z","snapshot_observed_at":"2026-08-07T17:59:20.917639Z","submitted_at":"2025-02-21T08:43:50Z","title":"Comparative Analysis of Black Hole Mass Estimation in Type-2 AGNs: Classical vs. Quantum Machine Learning and Deep Learning Approaches","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.15297","snapshot_observed_at":"2026-08-04T07:43:30.780775Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.24598","last_updated":"2026-07-31T02:29:01Z","snapshot_observed_at":"2026-08-05T23:09:37.535990Z","submitted_at":"2025-10-28T16:27:10Z","title":"A Novel XAI-Enhanced Quantum Adversarial Networks for Velocity Dispersion Modeling in MaNGA Galaxies","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T07:43:30.780775Z"},"links":{"cited_paper":"/paper/2502.15297","citing_paper":"/paper/2510.24598"},"observation_digest":"sha256:0bb59aa9c2c87eb555b36f143e43c0f87991b0e22cf11287fa8ca50b1759dea9","observation_id":"c11df991-2a92-41d6-b83b-b3377250dd73","resolution":{"observed_at":"2026-08-04T07:43:30.780775Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.15297/citation-record","integrity":"/paper/2502.15297/integrity","json":"/paper/2502.15297/citation-record.json","paper":"/paper/2502.15297"},"outbound":[],"paper":{"arxiv_id":"2502.15297","last_updated":"2025-02-24T07:30:05Z","latest_version":2,"primary_category":"astro-ph.IM","snapshot_observed_at":"2026-08-07T17:59:20.917639Z","submitted_at":"2025-02-21T08:43:50Z","title":"Comparative Analysis of Black Hole Mass Estimation in Type-2 AGNs: Classical vs. Quantum Machine Learning and Deep Learning Approaches"},"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:2502.15297."}