{"as_of":"2026-08-09T00:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a3354569164c50ef93cb311e620ebe33b2c8018f32242207d9db99398f400800","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":"2026-08-08T06:32:00.761636+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":"2026-08-07T14:09:32.364738Z","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":"2026-08-07T14:09:35.095595Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2307.16236","last_updated":"2023-07-30T13:58:46Z","snapshot_observed_at":"2026-08-05T06:04:57.052616Z","submitted_at":"2023-07-30T13:58:46Z","title":"Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey","version":1},"cited_work":{"arxiv_id":"2307.16236","doi":null,"metadata_source":"pith","pith_arxiv_id":"2307.16236","snapshot_observed_at":"2026-08-07T14:09:35.095595Z","title":"Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey","venue":"cs.NE","work_id":"30424bff-16e0-41e7-8afa-eb533065a490","year":2023},"citing_paper":{"arxiv_id":"2505.19928","last_updated":"2025-05-26T12:55:27Z","snapshot_observed_at":"2026-08-08T11:16:13.922243Z","submitted_at":"2025-05-26T12:55:27Z","title":"CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T14:09:32.364738Z"},"links":{"cited_paper":"/paper/2307.16236","citing_paper":"/paper/2505.19928"},"observation_digest":"sha256:70c0bdd7c2e01b7786bdd837a807da78c323e09f0d78a31cda8fd8834a191a91","observation_id":"408de803-5924-4c9f-bd93-867c94aa970f","resolution":{"observed_at":"2026-08-07T14:09:35.175066Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2307.16236/citation-record","integrity":"/paper/2307.16236/integrity","json":"/paper/2307.16236/citation-record.json","paper":"/paper/2307.16236"},"outbound":[],"paper":{"arxiv_id":"2307.16236","last_updated":"2023-07-30T13:58:46Z","latest_version":1,"primary_category":"cs.NE","snapshot_observed_at":"2026-08-05T06:04:57.052616Z","submitted_at":"2023-07-30T13:58:46Z","title":"Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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:2307.16236."}