{"as_of":"2026-08-08T16:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2404285ecc76f12858ff2b989c54c6c6f4e86f930cd775c81ac3ffe186b27072","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":"2026-08-07T11:27:51.378394Z","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":"2026-08-07T18:16:16.850658Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2001.05720","last_updated":"2020-01-16T10:00:26Z","snapshot_observed_at":"2026-08-08T11:47:36.530946Z","submitted_at":"2020-01-16T10:00:26Z","title":"Deep ICE: A Deep learning approach for MRI Intracranial Cavity Extraction","version":1},"cited_work":{"arxiv_id":"2001.05720","doi":"10.48550/arxiv.2001.05720","metadata_source":"pith","pith_arxiv_id":"2001.05720","snapshot_observed_at":"2026-08-07T18:16:16.850658Z","title":"Deep ICE: A Deep learning approach for MRI Intracranial Cavity Extraction","venue":"q-bio.QM","work_id":"d8837028-b3b7-4666-b163-18fe9fba0100","year":2020},"citing_paper":{"arxiv_id":"2506.03217","last_updated":"2025-07-15T14:08:11Z","snapshot_observed_at":"2026-08-07T11:19:28.576395Z","submitted_at":"2025-06-03T07:44:04Z","title":"petBrain: A New Pipeline for Amyloid, Tau Tangles and Neurodegeneration Quantification Using PET and MRI","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:27:51.378394Z"},"links":{"cited_paper":"/paper/2001.05720","citing_paper":"/paper/2506.03217"},"observation_digest":"sha256:a0febfdc2dfa66713252a61948c69eb4214afd51a1dc3402f573f8c5d82edb64","observation_id":"dfcac04b-b839-44f5-84cc-4400347473d5","resolution":{"observed_at":"2026-08-07T11:27:51.454896Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2001.05720/citation-record","integrity":"/paper/2001.05720/integrity","json":"/paper/2001.05720/citation-record.json","paper":"/paper/2001.05720"},"outbound":[],"paper":{"arxiv_id":"2001.05720","last_updated":"2020-01-16T10:00:26Z","latest_version":1,"primary_category":"q-bio.QM","snapshot_observed_at":"2026-08-08T11:47:36.530946Z","submitted_at":"2020-01-16T10:00:26Z","title":"Deep ICE: A Deep learning approach for MRI Intracranial Cavity Extraction"},"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 1 inbound Pith citation observation for arXiv:2001.05720."}