{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LEIDWSBXTX6JFXVS54OU7MQZ5F","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":"67749c5c5a13378ed5dcda66e11ee94f806f4e0e3ec2670c0dd59e6191c33e5f","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-06-30T10:24:29Z","title_canon_sha256":"b61ab4edb223dedbe0a162405d552b6a9f8708ca9b49ef9931cf85f78062176c"},"schema_version":"1.0","source":{"id":"2506.23700","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.23700","created_at":"2026-05-26T02:03:52Z"},{"alias_kind":"arxiv_version","alias_value":"2506.23700v2","created_at":"2026-05-26T02:03:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.23700","created_at":"2026-05-26T02:03:52Z"},{"alias_kind":"pith_short_12","alias_value":"LEIDWSBXTX6J","created_at":"2026-05-26T02:03:52Z"},{"alias_kind":"pith_short_16","alias_value":"LEIDWSBXTX6JFXVS","created_at":"2026-05-26T02:03:52Z"},{"alias_kind":"pith_short_8","alias_value":"LEIDWSBX","created_at":"2026-05-26T02:03:52Z"}],"graph_snapshots":[{"event_id":"sha256:12397606b4e8cafaf096d73025e7f5f7b4bcfa16f1708bbc3f88dc0c34cfefe2","target":"graph","created_at":"2026-05-26T02:03:52Z","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/2506.23700/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Medical image segmentation plays a crucial role in clinical diagnosis and treatment planning, where accurate boundary delineation is essential for precise lesion localization, organ identification, and quantitative assessment. In recent years, deep learning-based methods have significantly advanced segmentation accuracy. However, two major challenges remain. First, the performance of these methods heavily relies on large-scale annotated datasets, which are often difficult to obtain in medical scenarios due to privacy concerns and high annotation costs. Second, clinically challenging scenarios,","authors_text":"Fan Li, Haixia Bi, Peiting Tian, Xi Chen","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-06-30T10:24:29Z","title":"MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.23700","kind":"arxiv","version":2},"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:df4492732bafe7d9f21bdf0929cfb579ac59230cc7f2c2317300d6094f55a13b","target":"record","created_at":"2026-05-26T02:03:52Z","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":"67749c5c5a13378ed5dcda66e11ee94f806f4e0e3ec2670c0dd59e6191c33e5f","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2025-06-30T10:24:29Z","title_canon_sha256":"b61ab4edb223dedbe0a162405d552b6a9f8708ca9b49ef9931cf85f78062176c"},"schema_version":"1.0","source":{"id":"2506.23700","kind":"arxiv","version":2}},"canonical_sha256":"59103b48379dfc92deb2ef1d4fb219e9696bfcfea2c758cb16ec060c450935f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59103b48379dfc92deb2ef1d4fb219e9696bfcfea2c758cb16ec060c450935f6","first_computed_at":"2026-05-26T02:03:52.302748Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:03:52.302748Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wQy8o00XQFfZ+kluJcY0JcYmqPI6x8zSOYFACHDMmmoF8qh/L91orm5VXZ1jHp6paPwMxTAqUhFVyLfSxYvhDw==","signature_status":"signed_v1","signed_at":"2026-05-26T02:03:52.303790Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.23700","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:df4492732bafe7d9f21bdf0929cfb579ac59230cc7f2c2317300d6094f55a13b","sha256:12397606b4e8cafaf096d73025e7f5f7b4bcfa16f1708bbc3f88dc0c34cfefe2"],"state_sha256":"d8375a8a3ce5b1e4d2cdb98f38e2355a4e3b45b74b7d0c07592d5d2578c9f7b1"}