{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WYGIRHJJXVXHH2HP6U4JP25PH3","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":"9770c12b82a685c0c940334f4a2be5070c440bd2be9eb40a2e343665e3a134b1","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-bio.QM","submitted_at":"2026-06-21T18:56:42Z","title_canon_sha256":"233fda83e3cb41ec5ed76b81e3918b1e8839f3fc527d8834ce643d483ff8b043"},"schema_version":"1.0","source":{"id":"2606.23744","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23744","created_at":"2026-06-24T00:14:24Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23744v1","created_at":"2026-06-24T00:14:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23744","created_at":"2026-06-24T00:14:24Z"},{"alias_kind":"pith_short_12","alias_value":"WYGIRHJJXVXH","created_at":"2026-06-24T00:14:24Z"},{"alias_kind":"pith_short_16","alias_value":"WYGIRHJJXVXHH2HP","created_at":"2026-06-24T00:14:24Z"},{"alias_kind":"pith_short_8","alias_value":"WYGIRHJJ","created_at":"2026-06-24T00:14:24Z"}],"graph_snapshots":[{"event_id":"sha256:fc795e96ffc29bcac5544a677389e651d62089ccfb11d444096900edb8a5ea1d","target":"graph","created_at":"2026-06-24T00:14:24Z","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/2606.23744/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning has become an important tool in computational pathology, enabling automated analysis of histopathological images. While convolutional neural networks (CNNs) have traditionally dominated this field, transformer-based and hybrid architectures have recently demonstrated promising performance. However, comprehensive comparisons of these approaches for colorectal histopathology remain limited. This study evaluated twelve ImageNet-pretrained CNN, transformer, and hybrid architectures using the Kather colorectal histopathology dataset containing 5,000 image tiles from eight tissue class","authors_text":"Reza Bozorgpour","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-bio.QM","submitted_at":"2026-06-21T18:56:42Z","title":"Performance and Interpretability of Convolutional, Transformer, and Hybrid Deep Learning Models in Colorectal Histology Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23744","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:d3a7bf508b503fb4196cd65662d6cedb3c6a7a7342064d12665334aa06db81d4","target":"record","created_at":"2026-06-24T00:14:24Z","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":"9770c12b82a685c0c940334f4a2be5070c440bd2be9eb40a2e343665e3a134b1","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"q-bio.QM","submitted_at":"2026-06-21T18:56:42Z","title_canon_sha256":"233fda83e3cb41ec5ed76b81e3918b1e8839f3fc527d8834ce643d483ff8b043"},"schema_version":"1.0","source":{"id":"2606.23744","kind":"arxiv","version":1}},"canonical_sha256":"b60c889d29bd6e73e8eff53897ebaf3ec19a88afa7c9af7ca7c738a08f65bd53","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b60c889d29bd6e73e8eff53897ebaf3ec19a88afa7c9af7ca7c738a08f65bd53","first_computed_at":"2026-06-24T00:14:24.866208Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-24T00:14:24.866208Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Zzr3FhkCsFBftpHbWkfjOyhLgz4nxHM47BH1Jytaq5OhdSB3Qf/mlv4EJQNEJBluNeFrtf6jXjgnQZtm9Os/Bg==","signature_status":"signed_v1","signed_at":"2026-06-24T00:14:24.866654Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.23744","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d3a7bf508b503fb4196cd65662d6cedb3c6a7a7342064d12665334aa06db81d4","sha256:fc795e96ffc29bcac5544a677389e651d62089ccfb11d444096900edb8a5ea1d"],"state_sha256":"693786f28338e354f87dd21993f91a8700e7c6948c4aa66d1127e15a70152e05"}