{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:GHYW5ZEEKNAY6VT6TXCJPZBQYG","short_pith_number":"pith:GHYW5ZEE","canonical_record":{"source":{"id":"2312.02366","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-04T21:47:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"18924c631473d30b9a36c3df3230f38e0673ad68d3f0589eb34666e75909b463","abstract_canon_sha256":"29a1905c6e4b81e6ca337709d553b228709117eabbc195f45d57a9e943533464"},"schema_version":"1.0"},"canonical_sha256":"31f16ee48453418f567e9dc497e430c19d27f4b7f74b2fea64ceeb51c6b3f676","source":{"kind":"arxiv","id":"2312.02366","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.02366","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"arxiv_version","alias_value":"2312.02366v4","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.02366","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"pith_short_12","alias_value":"GHYW5ZEEKNAY","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"pith_short_16","alias_value":"GHYW5ZEEKNAY6VT6","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"pith_short_8","alias_value":"GHYW5ZEE","created_at":"2026-07-05T09:06:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:GHYW5ZEEKNAY6VT6TXCJPZBQYG","target":"record","payload":{"canonical_record":{"source":{"id":"2312.02366","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-04T21:47:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"18924c631473d30b9a36c3df3230f38e0673ad68d3f0589eb34666e75909b463","abstract_canon_sha256":"29a1905c6e4b81e6ca337709d553b228709117eabbc195f45d57a9e943533464"},"schema_version":"1.0"},"canonical_sha256":"31f16ee48453418f567e9dc497e430c19d27f4b7f74b2fea64ceeb51c6b3f676","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:06:56.395266Z","signature_b64":"eCqfrkRcQmDgP5GE5Yu85e20Pbsa6Hlj7zw44l+N2vejtYl2GQhkV4fMYXXUlSzWfl4wZlf0MSDexQ00+rhzCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"31f16ee48453418f567e9dc497e430c19d27f4b7f74b2fea64ceeb51c6b3f676","last_reissued_at":"2026-07-05T09:06:56.394834Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:06:56.394834Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.02366","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:06:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EjqIa991n6j9bmMKNkyZSbD6UI3aRfMmAgS3U9VTN2tjO8UfBuWLQlYqaMTnXkT0iDC1ajrDMFsSMldpSOIWDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:52:36.002204Z"},"content_sha256":"7b770314f01c62b2efa0a9952eb4432c104ee3adb229c17203647e7ccebd34bc","schema_version":"1.0","event_id":"sha256:7b770314f01c62b2efa0a9952eb4432c104ee3adb229c17203647e7ccebd34bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:GHYW5ZEEKNAY6VT6TXCJPZBQYG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Abdulrhman Aljouie, Jiahong Ouyang, Mohammed Baharoon, Waseem Qureshi, Wei Peng, Yanwu Xu","submitted_at":"2023-12-04T21:47:10Z","abstract_excerpt":"The integration of deep learning systems into healthcare has been hindered by the resource-intensive process of data annotation and the inability of these systems to generalize to different data distributions. Foundation models, which are models pre-trained on large datasets, have emerged as a solution to reduce reliance on annotated data and enhance model generalizability and robustness. DINOv2 is an open-source foundation model pre-trained with self-supervised learning on 142 million curated natural images that exhibits promising capabilities across various vision tasks. Nevertheless, a crit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02366","kind":"arxiv","version":4},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2312.02366/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:06:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A90iVlZowAQ0mVIKQvaOS+1nDmq6xFwbRtawaYBkv/DlEzIcp/M1nfR9zJg5eF6AXmvUlOg3kDvn9jXa2O1bAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:52:36.002775Z"},"content_sha256":"ef60b946dc36f426aca8268115585bb21b7cac502e61d1fdfc92a635cf435ad4","schema_version":"1.0","event_id":"sha256:ef60b946dc36f426aca8268115585bb21b7cac502e61d1fdfc92a635cf435ad4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GHYW5ZEEKNAY6VT6TXCJPZBQYG/bundle.json","state_url":"https://pith.science/pith/GHYW5ZEEKNAY6VT6TXCJPZBQYG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GHYW5ZEEKNAY6VT6TXCJPZBQYG/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-04T08:52:36Z","links":{"resolver":"https://pith.science/pith/GHYW5ZEEKNAY6VT6TXCJPZBQYG","bundle":"https://pith.science/pith/GHYW5ZEEKNAY6VT6TXCJPZBQYG/bundle.json","state":"https://pith.science/pith/GHYW5ZEEKNAY6VT6TXCJPZBQYG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GHYW5ZEEKNAY6VT6TXCJPZBQYG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:GHYW5ZEEKNAY6VT6TXCJPZBQYG","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":"29a1905c6e4b81e6ca337709d553b228709117eabbc195f45d57a9e943533464","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-04T21:47:10Z","title_canon_sha256":"18924c631473d30b9a36c3df3230f38e0673ad68d3f0589eb34666e75909b463"},"schema_version":"1.0","source":{"id":"2312.02366","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.02366","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"arxiv_version","alias_value":"2312.02366v4","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.02366","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"pith_short_12","alias_value":"GHYW5ZEEKNAY","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"pith_short_16","alias_value":"GHYW5ZEEKNAY6VT6","created_at":"2026-07-05T09:06:56Z"},{"alias_kind":"pith_short_8","alias_value":"GHYW5ZEE","created_at":"2026-07-05T09:06:56Z"}],"graph_snapshots":[{"event_id":"sha256:ef60b946dc36f426aca8268115585bb21b7cac502e61d1fdfc92a635cf435ad4","target":"graph","created_at":"2026-07-05T09:06:56Z","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/2312.02366/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The integration of deep learning systems into healthcare has been hindered by the resource-intensive process of data annotation and the inability of these systems to generalize to different data distributions. Foundation models, which are models pre-trained on large datasets, have emerged as a solution to reduce reliance on annotated data and enhance model generalizability and robustness. DINOv2 is an open-source foundation model pre-trained with self-supervised learning on 142 million curated natural images that exhibits promising capabilities across various vision tasks. Nevertheless, a crit","authors_text":"Abdulrhman Aljouie, Jiahong Ouyang, Mohammed Baharoon, Waseem Qureshi, Wei Peng, Yanwu Xu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-04T21:47:10Z","title":"Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology Benchmarks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.02366","kind":"arxiv","version":4},"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":"sha256:7b770314f01c62b2efa0a9952eb4432c104ee3adb229c17203647e7ccebd34bc","target":"record","created_at":"2026-07-05T09:06:56Z","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":"29a1905c6e4b81e6ca337709d553b228709117eabbc195f45d57a9e943533464","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-04T21:47:10Z","title_canon_sha256":"18924c631473d30b9a36c3df3230f38e0673ad68d3f0589eb34666e75909b463"},"schema_version":"1.0","source":{"id":"2312.02366","kind":"arxiv","version":4}},"canonical_sha256":"31f16ee48453418f567e9dc497e430c19d27f4b7f74b2fea64ceeb51c6b3f676","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"31f16ee48453418f567e9dc497e430c19d27f4b7f74b2fea64ceeb51c6b3f676","first_computed_at":"2026-07-05T09:06:56.394834Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:06:56.394834Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eCqfrkRcQmDgP5GE5Yu85e20Pbsa6Hlj7zw44l+N2vejtYl2GQhkV4fMYXXUlSzWfl4wZlf0MSDexQ00+rhzCw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:06:56.395266Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.02366","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7b770314f01c62b2efa0a9952eb4432c104ee3adb229c17203647e7ccebd34bc","sha256:ef60b946dc36f426aca8268115585bb21b7cac502e61d1fdfc92a635cf435ad4"],"state_sha256":"2db7c8541195b43eed6ba802f7fe0851a20dbe2b754556375e78353ee64b72a5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xjfPYnUw1MeZ1BMB5Ds5i05MhhjgfsaY0JiVX7zkMI7y1b3BucQErAldiWQJ5UJmLx59EDBMY8MxOWIX3KTtDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T08:52:36.007012Z","bundle_sha256":"dc187ca8c0c06923fca91334a5f6a1a417b639e0c08616fb0f988faa37e82f38"}}