{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HXGE3JWXHPD7LF35HCU67UQZ7D","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":"1f2af59dca002ee80d3e4d39d0f4fb97d0b130692ea32a057a1e574a3ef64501","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-19T02:13:07Z","title_canon_sha256":"abe4300c3364e560153eba65b9ed3ed1eb602dbc1cbc210c77aab8eefd7b0193"},"schema_version":"1.0","source":{"id":"2504.14139","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.14139","created_at":"2026-07-05T10:54:47Z"},{"alias_kind":"arxiv_version","alias_value":"2504.14139v2","created_at":"2026-07-05T10:54:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.14139","created_at":"2026-07-05T10:54:47Z"},{"alias_kind":"pith_short_12","alias_value":"HXGE3JWXHPD7","created_at":"2026-07-05T10:54:47Z"},{"alias_kind":"pith_short_16","alias_value":"HXGE3JWXHPD7LF35","created_at":"2026-07-05T10:54:47Z"},{"alias_kind":"pith_short_8","alias_value":"HXGE3JWX","created_at":"2026-07-05T10:54:47Z"}],"graph_snapshots":[{"event_id":"sha256:a3222466624c4e6960d978782ad1e9fab8a0b6852c4fb398b4c16d458ebf61c3","target":"graph","created_at":"2026-07-05T10:54:47Z","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/2504.14139/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Background: Automated classification of thyroid Fine Needle Aspiration Biopsy (FNAB) images faces challenges in limited data, inter-observer variability, and computational cost. Efficient, interpretable models are crucial for clinical support.\n  Objective: To develop and externally validate a deep learning system for multi-class thyroid FNAB image classification into three key categories directly guiding post-biopsy treatment in Vietnam: Benign (Bethesda II), Indeterminate/Suspicious (BI, III, IV, V), and Malignant (BVI), achieving high diagnostic accuracy with low computational overhead.\n  Me","authors_text":"De Nguyen-Van, Dung Vu-Tien, Hai Pham-Ngoc, Phuong Le-Hong","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-19T02:13:07Z","title":"ThyroidEffi 1.0: A Cost-Effective System for High-Performance Multi-Class Thyroid Carcinoma Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.14139","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":"sha256:1582b10dc36547c201a625c2672f7a2a747bc5e951f23ebd9d57a2ed3f37984b","target":"record","created_at":"2026-07-05T10:54:47Z","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":"1f2af59dca002ee80d3e4d39d0f4fb97d0b130692ea32a057a1e574a3ef64501","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-19T02:13:07Z","title_canon_sha256":"abe4300c3364e560153eba65b9ed3ed1eb602dbc1cbc210c77aab8eefd7b0193"},"schema_version":"1.0","source":{"id":"2504.14139","kind":"arxiv","version":2}},"canonical_sha256":"3dcc4da6d73bc7f5977d38a9efd219f8cdd9130e5d31d9ceb62dfdb730f3c4ee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3dcc4da6d73bc7f5977d38a9efd219f8cdd9130e5d31d9ceb62dfdb730f3c4ee","first_computed_at":"2026-07-05T10:54:47.025582Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:54:47.025582Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KBJUfWejt0eMMGbSpJGwoyjt0cvSHt/8ANcPlXSgPghlT0nq8GudWdBgjVLzReh/sgR3WOgN2SmQUpSFXgQcAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:54:47.026009Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.14139","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1582b10dc36547c201a625c2672f7a2a747bc5e951f23ebd9d57a2ed3f37984b","sha256:a3222466624c4e6960d978782ad1e9fab8a0b6852c4fb398b4c16d458ebf61c3"],"state_sha256":"c50e4b8ad0891d953a629ec8b84e3fbbf5c3be05795943ccaac73df65909fe91"}