{"as_of":"2026-08-08T18:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f00c1e353553060397c066a5517834d58871414f4f3a44f02bdfb0ebe5565c92","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:24:50.824811Z","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":"2026-08-06T14:24:51.806762Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.01948","last_updated":"2024-07-02T04:39:19Z","snapshot_observed_at":"2026-08-07T04:49:44.329056Z","submitted_at":"2024-07-02T04:39:19Z","title":"Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01948","snapshot_observed_at":"2026-08-07T05:24:50.824811Z","title":"Extracting and encoding: Leveraging large language models and medical knowledge to enhance radiological text representation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-07T05:18:44.380661Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.824811Z"},"links":{"cited_paper":"/paper/2407.01948","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:c7f7fbfd522f88914aeed036d7639634b6eab939ca9a13175be347b5830aa017","observation_id":"7a4825d3-1e66-40d3-a024-93d598a9168b","resolution":{"observed_at":"2026-08-07T05:24:50.824811Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01948","last_updated":"2024-07-02T04:39:19Z","snapshot_observed_at":"2026-08-07T04:49:44.329056Z","submitted_at":"2024-07-02T04:39:19Z","title":"Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation","version":1},"cited_work":{"arxiv_id":"2407.01948","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.01948","snapshot_observed_at":"2026-08-06T14:24:51.806762Z","title":"Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation","venue":"cs.CL","work_id":"88b60219-9371-4e13-8483-96a6dfc1f3a4","year":2024},"citing_paper":{"arxiv_id":"2507.19398","last_updated":"2025-07-25T16:05:47Z","snapshot_observed_at":"2026-08-08T12:46:31.767301Z","submitted_at":"2025-07-25T16:05:47Z","title":"CXR-CML: Improved zero-shot classification of long-tailed multi-label diseases in Chest X-Rays","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T14:24:51.255176Z"},"links":{"cited_paper":"/paper/2407.01948","citing_paper":"/paper/2507.19398"},"observation_digest":"sha256:1f9c44c32cbff66e2b03e34bfce1f231e1e502eb0d1e1ae7a5f5bb2bcf93856b","observation_id":"17e021de-b825-49c5-9995-74a2ca43022d","resolution":{"observed_at":"2026-08-06T14:24:51.812069Z","resolver_source":"local_arxiv","status":"verified_exact"},"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"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01948","last_updated":"2024-07-02T04:39:19Z","snapshot_observed_at":"2026-08-07T04:49:44.329056Z","submitted_at":"2024-07-02T04:39:19Z","title":"Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01948","snapshot_observed_at":"2026-08-03T08:57:18.058411Z","title":"Extracting and encoding: Lever- aging large language models and medical knowledge to enhance radiological text representation.arXiv preprint arXiv:2407.01948, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2601.15408","last_updated":"2026-06-06T22:36:23Z","snapshot_observed_at":"2026-08-03T08:57:16.556473Z","submitted_at":"2026-01-21T19:19:41Z","title":"CURE: Curriculum-guided Multi-task Training for Reliable Anatomy Grounded Report Generation","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-03T08:57:18.058411Z"},"links":{"cited_paper":"/paper/2407.01948","citing_paper":"/paper/2601.15408"},"observation_digest":"sha256:5f32de13227122f44ef9cc1f985057f81731313b0e22d284d9070f89adc7289b","observation_id":"d11fe0d5-49c2-4ddb-ad39-0f1847492e04","resolution":{"observed_at":"2026-08-03T08:57:18.058411Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2407.01948/citation-record","integrity":"/paper/2407.01948/integrity","json":"/paper/2407.01948/citation-record.json","paper":"/paper/2407.01948"},"outbound":[],"paper":{"arxiv_id":"2407.01948","last_updated":"2024-07-02T04:39:19Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T04:49:44.329056Z","submitted_at":"2024-07-02T04:39:19Z","title":"Extracting and Encoding: Leveraging Large Language Models and Medical Knowledge to Enhance Radiological Text Representation"},"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 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.01948."}