{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:MVEOZG4UTOO5PAMEVBDEXQ3YEA","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":"b3372b8a2338fd9a4b5b34f0b1db3909e6ff22fb242c708019469172ae2595c0","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-10T21:40:19Z","title_canon_sha256":"438470d20afc790f6f886b886e1ed8faf8fc3d1a6291ae77d07d9a2534522986"},"schema_version":"1.0","source":{"id":"2310.07033","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.07033","created_at":"2026-07-05T06:59:39Z"},{"alias_kind":"arxiv_version","alias_value":"2310.07033v1","created_at":"2026-07-05T06:59:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.07033","created_at":"2026-07-05T06:59:39Z"},{"alias_kind":"pith_short_12","alias_value":"MVEOZG4UTOO5","created_at":"2026-07-05T06:59:39Z"},{"alias_kind":"pith_short_16","alias_value":"MVEOZG4UTOO5PAME","created_at":"2026-07-05T06:59:39Z"},{"alias_kind":"pith_short_8","alias_value":"MVEOZG4U","created_at":"2026-07-05T06:59:39Z"}],"graph_snapshots":[{"event_id":"sha256:3b459b1f3e33ca59cf79a0473575a5ac1ca8f5dbd14d59fade0cb84333215a81","target":"graph","created_at":"2026-07-05T06:59:39Z","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/2310.07033/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent breakthroughs in self-supervised learning have enabled the use of large unlabeled datasets to train visual foundation models that can generalize to a variety of downstream tasks. While this training paradigm is well suited for the medical domain where annotations are scarce, large-scale pre-training in the medical domain, and in particular pathology, has not been extensively studied. Previous work in self-supervised learning in pathology has leveraged smaller datasets for both pre-training and evaluating downstream performance. The aim of this project is to train the largest academic fo","authors_text":"Adam Schoenfeld, Alexandros D. Polydorides, Aryeh Stock, Brandon Veremis, Carlos Cordon-Cardo, Chad Vanderbilt, Cyrus Hedvat, Eugene Fluder, Gabriele Campanella, Jennifer Zeng, Patricia Kovatch, Ricky Kwan, Thomas J. Fuchs","cross_cats":["cs.AI","cs.LG","eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-10T21:40:19Z","title":"Computational Pathology at Health System Scale -- Self-Supervised Foundation Models from Three Billion Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.07033","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:c46e435827f821d221ac70ddd2a5f3f04ca49332940c92ce3e3d80d1587154a7","target":"record","created_at":"2026-07-05T06:59:39Z","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":"b3372b8a2338fd9a4b5b34f0b1db3909e6ff22fb242c708019469172ae2595c0","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-10-10T21:40:19Z","title_canon_sha256":"438470d20afc790f6f886b886e1ed8faf8fc3d1a6291ae77d07d9a2534522986"},"schema_version":"1.0","source":{"id":"2310.07033","kind":"arxiv","version":1}},"canonical_sha256":"6548ec9b949b9dd78184a8464bc3782011215f12b3b77d9a01857a19a5b2ed21","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6548ec9b949b9dd78184a8464bc3782011215f12b3b77d9a01857a19a5b2ed21","first_computed_at":"2026-07-05T06:59:39.907460Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:59:39.907460Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"OuDzTPQtdlz+Fvw/tWY/zTUdwyD/MhmtqT4UZZ9DKN1o6lf2XMWbiqnoFY980mm8f6f2X941obiQKMuan8AaBg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:59:39.907866Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.07033","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c46e435827f821d221ac70ddd2a5f3f04ca49332940c92ce3e3d80d1587154a7","sha256:3b459b1f3e33ca59cf79a0473575a5ac1ca8f5dbd14d59fade0cb84333215a81"],"state_sha256":"efc491e020c7467f23e3038090bcf7c09da2a91a46c2792b6cf9e135ebff7710"}