{"as_of":"2026-08-09T15:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:eadaa2209f120f35ea87a9e35dc735111d2750acd2231c42c485e437fda83799","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":"2026-08-06T17:47:04.412066Z","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":"2026-08-06T17:47:04.785221Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1909.04087","last_updated":"2020-11-13T19:00:09Z","snapshot_observed_at":"2026-08-09T04:03:10.445249Z","submitted_at":"2019-09-09T18:17:10Z","title":"Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images","version":3},"cited_work":{"arxiv_id":"1909.04087","doi":null,"metadata_source":"pith","pith_arxiv_id":"1909.04087","snapshot_observed_at":"2026-08-06T17:47:04.785221Z","title":"Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images","venue":"eess.IV","work_id":"759a1bb4-3c66-4771-95ac-c9f540f77a50","year":2019},"citing_paper":{"arxiv_id":"2507.10194","last_updated":"2025-07-14T12:01:08Z","snapshot_observed_at":"2026-08-08T10:55:09.891170Z","submitted_at":"2025-07-14T12:01:08Z","title":"Learning Private Representations through Entropy-based Adversarial Training","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T17:47:04.412066Z"},"links":{"cited_paper":"/paper/1909.04087","citing_paper":"/paper/2507.10194"},"observation_digest":"sha256:102bfa543600f19df1676af06e9dd431ecebfbcdcc22f108ee172fafdc7b036f","observation_id":"131b5ba8-2cfc-404c-8874-b202aada41ef","resolution":{"observed_at":"2026-08-06T17:47:04.789435Z","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/1909.04087/citation-record","integrity":"/paper/1909.04087/integrity","json":"/paper/1909.04087/citation-record.json","paper":"/paper/1909.04087"},"outbound":[],"paper":{"arxiv_id":"1909.04087","last_updated":"2020-11-13T19:00:09Z","latest_version":3,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-09T04:03:10.445249Z","submitted_at":"2019-09-09T18:17:10Z","title":"Privacy-Net: An Adversarial Approach for Identity-Obfuscated Segmentation of Medical Images"},"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:1909.04087."}