{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:AOYFU6BTH52IMBFCS3GOEACC5C","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":"3752b9213e446939a36a1493c688c959f43c8a95baedf52e3301e52f5dd626f3","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-02T10:41:42Z","title_canon_sha256":"631682ed192ff434a0bfcd4f9efc7a18e792d0db1b4e67fa1b5751d6b12967cc"},"schema_version":"1.0","source":{"id":"2311.01138","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.01138","created_at":"2026-07-05T07:08:21Z"},{"alias_kind":"arxiv_version","alias_value":"2311.01138v1","created_at":"2026-07-05T07:08:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.01138","created_at":"2026-07-05T07:08:21Z"},{"alias_kind":"pith_short_12","alias_value":"AOYFU6BTH52I","created_at":"2026-07-05T07:08:21Z"},{"alias_kind":"pith_short_16","alias_value":"AOYFU6BTH52IMBFC","created_at":"2026-07-05T07:08:21Z"},{"alias_kind":"pith_short_8","alias_value":"AOYFU6BT","created_at":"2026-07-05T07:08:21Z"}],"graph_snapshots":[{"event_id":"sha256:d8921262714c7c60369fd7f53ffd31ad8f132422edb80dfa67e1989d08074eb4","target":"graph","created_at":"2026-07-05T07:08:21Z","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/2311.01138/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To improve the prognosis of patients suffering from pulmonary diseases, such as lung cancer, early diagnosis and treatment are crucial. The analysis of CT images is invaluable for diagnosis, whereas high quality segmentation of the airway tree are required for intervention planning and live guidance during bronchoscopy. Recently, the Multi-domain Airway Tree Modeling (ATM'22) challenge released a large dataset, both enabling training of deep-learning based models and bringing substantial improvement of the state-of-the-art for the airway segmentation task. However, the ATM'22 dataset includes ","authors_text":"Andre Pedersen, David Bouget, Erlend Fagertun Hofstad, H{\\aa}kon Olav Leira, Karen-Helene St{\\o}verud, Thomas Lang{\\o}","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-02T10:41:42Z","title":"AeroPath: An airway segmentation benchmark dataset with challenging pathology"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.01138","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":"sha256:55ab4efa62200906add9348009a92eab970dd7ccc70978d9bfb19d549c45ca8a","target":"record","created_at":"2026-07-05T07:08:21Z","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":"3752b9213e446939a36a1493c688c959f43c8a95baedf52e3301e52f5dd626f3","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-02T10:41:42Z","title_canon_sha256":"631682ed192ff434a0bfcd4f9efc7a18e792d0db1b4e67fa1b5751d6b12967cc"},"schema_version":"1.0","source":{"id":"2311.01138","kind":"arxiv","version":1}},"canonical_sha256":"03b05a78333f748604a296cce20042e8845d4e820aacfa3bc5f1367a8103f80e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"03b05a78333f748604a296cce20042e8845d4e820aacfa3bc5f1367a8103f80e","first_computed_at":"2026-07-05T07:08:21.392390Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:08:21.392390Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fpaUcTX4qYumRdjAhv6DDby/ePKkd3muuj8hskFG+kJGkHP1/D1vCE/emc0kskysAGopNtFur+BGioy3B9T8BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:08:21.392844Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.01138","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:55ab4efa62200906add9348009a92eab970dd7ccc70978d9bfb19d549c45ca8a","sha256:d8921262714c7c60369fd7f53ffd31ad8f132422edb80dfa67e1989d08074eb4"],"state_sha256":"ee9b2f536a527a45e9f11a9468d76f8b4b790aeb7e073eef5574c56faf65e3aa"}