{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:QXSNXDQDGU62KQCQC3HGIM5VPF","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"f8af2096ec70c46b95da9a7d4dbfa988024f9ff4a2aefca47dd6835c8453f176","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2026-01-11T19:40:34Z","title_canon_sha256":"956d4fd5a90332fd5cc58d134c366055a3e0d58cf1dff95fea0f0e688c9e83d4"},"schema_version":"1.0","source":{"id":"2601.07044","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.07044","created_at":"2026-05-26T01:02:30Z"},{"alias_kind":"arxiv_version","alias_value":"2601.07044v1","created_at":"2026-05-26T01:02:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.07044","created_at":"2026-05-26T01:02:30Z"},{"alias_kind":"pith_short_12","alias_value":"QXSNXDQDGU62","created_at":"2026-05-26T01:02:30Z"},{"alias_kind":"pith_short_16","alias_value":"QXSNXDQDGU62KQCQ","created_at":"2026-05-26T01:02:30Z"},{"alias_kind":"pith_short_8","alias_value":"QXSNXDQD","created_at":"2026-05-26T01:02:30Z"}],"graph_snapshots":[{"event_id":"sha256:88c11aa08e7d0b1b6a8603f7c955f70194aa4afea5ab9baccc9b2a5593c81112","target":"graph","created_at":"2026-05-26T01:02:30Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2601.07044/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Interval-censoring frequently occurs in studies of chronic diseases where disease status is inferred from intermittently collected biomarkers. Although many methods have been developed to analyze such data, they typically assume perfect disease diagnosis, which often does not hold in practice due to the inherent imperfect clinical diagnosis of cognitive functions or measurement errors of biomarkers such as cerebrospinal fluid. In this work, we introduce a semiparametric modeling framework using the Cox proportional hazards model to address interval-censored data in the presence of inaccurate d","authors_text":"Donglin Zeng, Yuanjia Wang, Yuhao Deng","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2026-01-11T19:40:34Z","title":"Semiparametric Analysis of Interval-Censored Data Subject to Inaccurate Diagnoses with A Terminal Event"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.07044","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:2ecd3bac6eb75eafab594fe4f0a961d7af149915c1fa9e9bd4fc7264c9f48ae8","target":"record","created_at":"2026-05-26T01:02:30Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"f8af2096ec70c46b95da9a7d4dbfa988024f9ff4a2aefca47dd6835c8453f176","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2026-01-11T19:40:34Z","title_canon_sha256":"956d4fd5a90332fd5cc58d134c366055a3e0d58cf1dff95fea0f0e688c9e83d4"},"schema_version":"1.0","source":{"id":"2601.07044","kind":"arxiv","version":1}},"canonical_sha256":"85e4db8e03353da5405016ce6433b57955a729b86896feff79bd5c19e1643934","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"85e4db8e03353da5405016ce6433b57955a729b86896feff79bd5c19e1643934","first_computed_at":"2026-05-26T01:02:30.619538Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T01:02:30.619538Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"x+FhUJhAdZ8jFa6WqeCT21bSNzOzIuSP8MlwQqly70nrgScRSG22bz75sW0olvdM+mzWxVYPfoDl8645d9/JCQ==","signature_status":"signed_v1","signed_at":"2026-05-26T01:02:30.620353Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.07044","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2ecd3bac6eb75eafab594fe4f0a961d7af149915c1fa9e9bd4fc7264c9f48ae8","sha256:88c11aa08e7d0b1b6a8603f7c955f70194aa4afea5ab9baccc9b2a5593c81112"],"state_sha256":"22744f343f87342f257a5c930f3161cebcd047bf1fe0444854599fcdcb84e1e3"}