{"as_of":"2026-08-15T07:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a87c4622da336901e180a224a5275ce535b0c4d7500aea05608f5e68767f7155","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":"2026-08-15T06:32:42.880941+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":"2026-08-11T14:41:10.300459Z","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":"2026-08-11T14:41:10.409475Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2109.04535","last_updated":"2021-09-09T19:48:57Z","snapshot_observed_at":"2026-08-13T18:14:21.524746Z","submitted_at":"2021-09-09T19:48:57Z","title":"Identifying Morality Frames in Political Tweets using Relational Learning","version":1},"cited_work":{"arxiv_id":"2109.04535","doi":null,"metadata_source":"pith","pith_arxiv_id":"2109.04535","snapshot_observed_at":"2026-08-11T14:41:10.409475Z","title":"Identifying Morality Frames in Political Tweets using Relational Learning","venue":"cs.CL","work_id":"101c1636-3f5b-472a-b302-75251bb731fe","year":2021},"citing_paper":{"arxiv_id":"2412.11745","last_updated":"2024-12-19T15:55:45Z","snapshot_observed_at":"2026-08-13T06:38:23.479632Z","submitted_at":"2024-12-16T13:03:43Z","title":"Beyond Dataset Creation: Critical View of Annotation Variation and Bias Probing of a Dataset for Online Radical Content Detection","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T14:41:10.300459Z"},"links":{"cited_paper":"/paper/2109.04535","citing_paper":"/paper/2412.11745"},"observation_digest":"sha256:16d134a4e21a3ca784ef4fb9cbcffa4dea6b14c46bd493d183dd7d6e5d9fca1c","observation_id":"2370e15f-a920-45e4-931d-61b1fa1dd0f1","resolution":{"observed_at":"2026-08-11T14:41:10.413813Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2109.04535/citation-record","integrity":"/paper/2109.04535/integrity","json":"/paper/2109.04535/citation-record.json","paper":"/paper/2109.04535"},"outbound":[],"paper":{"arxiv_id":"2109.04535","last_updated":"2021-09-09T19:48:57Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-13T18:14:21.524746Z","submitted_at":"2021-09-09T19:48:57Z","title":"Identifying Morality Frames in Political Tweets using Relational Learning"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2109.04535."}