{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:3RX6455V7AORC6YGJJCUYVGSML","short_pith_number":"pith:3RX6455V","canonical_record":{"source":{"id":"2405.08786","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-05-14T17:35:27Z","cross_cats_sorted":[],"title_canon_sha256":"ecfef00ec757544e3c5a38c59c5e1b2142ebbc9ac9a2c57f78b4a1495901966e","abstract_canon_sha256":"baa65533d1e2de9b591f71cf96f20f0969f44ae40ddee1a76285ffd0ac305870"},"schema_version":"1.0"},"canonical_sha256":"dc6fee77b5f81d117b064a454c54d262e037edb0b6f690357f882b5b97a42f20","source":{"kind":"arxiv","id":"2405.08786","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.08786","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"arxiv_version","alias_value":"2405.08786v2","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.08786","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"pith_short_12","alias_value":"3RX6455V7AOR","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"pith_short_16","alias_value":"3RX6455V7AORC6YG","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"pith_short_8","alias_value":"3RX6455V","created_at":"2026-07-05T08:42:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:3RX6455V7AORC6YGJJCUYVGSML","target":"record","payload":{"canonical_record":{"source":{"id":"2405.08786","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-05-14T17:35:27Z","cross_cats_sorted":[],"title_canon_sha256":"ecfef00ec757544e3c5a38c59c5e1b2142ebbc9ac9a2c57f78b4a1495901966e","abstract_canon_sha256":"baa65533d1e2de9b591f71cf96f20f0969f44ae40ddee1a76285ffd0ac305870"},"schema_version":"1.0"},"canonical_sha256":"dc6fee77b5f81d117b064a454c54d262e037edb0b6f690357f882b5b97a42f20","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:42:04.252592Z","signature_b64":"bnkNHlL2ahZ27FDugFQYRyzSJmsUG4nLsA6NOjkPrhddwE8cMzRbnYcETNf5EhKPSkG5Dq828+VKwqkLtyNIDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dc6fee77b5f81d117b064a454c54d262e037edb0b6f690357f882b5b97a42f20","last_reissued_at":"2026-07-05T08:42:04.252106Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:42:04.252106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.08786","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:42:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DFHR1uRV8yZsURYQjbg4re4YOij9tecEtnW+Dc+jsz9MdP5z57B/mP9+5FfSA0Mj5hWIBWYhU2EUG+I9z8ORBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T17:05:44.341062Z"},"content_sha256":"f4b8e45c866e17451e4937dc5a88afd55f3eab7b90ab72c5b3b64aca7a1f0bbc","schema_version":"1.0","event_id":"sha256:f4b8e45c866e17451e4937dc5a88afd55f3eab7b90ab72c5b3b64aca7a1f0bbc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:3RX6455V7AORC6YGJJCUYVGSML","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Incorporating Clinical Guidelines through Adapting Multi-modal Large Language Model for Prostate Cancer PI-RADS Scoring","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aasa Feragen, Hongda Guo, Ka Fung Peter Chiu, Manxi Lin, Qi Dou, Tiantian Zhang, Xiaofan Zhang","submitted_at":"2024-05-14T17:35:27Z","abstract_excerpt":"The Prostate Imaging Reporting and Data System (PI-RADS) is pivotal in the diagnosis of clinically significant prostate cancer through MRI imaging. Current deep learning-based PI-RADS scoring methods often lack the incorporation of common PI-RADS clinical guideline~(PICG) utilized by radiologists, potentially compromising scoring accuracy. This paper introduces a novel approach that adapts a multi-modal large language model (MLLM) to incorporate PICG into PI-RADS scoring model without additional annotations and network parameters. We present a designed two-stage fine-tuning process aiming at a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.08786","kind":"arxiv","version":2},"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/2405.08786/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":"2026-07-05T08:42:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ao0lXxQHNcoMH/1Bp65uOOXVFJPy0qZ/G+A8eNnpS+dHtV46e790qm6mI1YXmjGgQz6PIiwjvWv+RX8//2EHBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T17:05:44.341558Z"},"content_sha256":"bb049dd4cc2251a622da2927000ffc2fbec1cf35551e9722c0de259c2c37e81e","schema_version":"1.0","event_id":"sha256:bb049dd4cc2251a622da2927000ffc2fbec1cf35551e9722c0de259c2c37e81e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3RX6455V7AORC6YGJJCUYVGSML/bundle.json","state_url":"https://pith.science/pith/3RX6455V7AORC6YGJJCUYVGSML/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3RX6455V7AORC6YGJJCUYVGSML/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":"2026-08-06T17:05:44Z","links":{"resolver":"https://pith.science/pith/3RX6455V7AORC6YGJJCUYVGSML","bundle":"https://pith.science/pith/3RX6455V7AORC6YGJJCUYVGSML/bundle.json","state":"https://pith.science/pith/3RX6455V7AORC6YGJJCUYVGSML/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3RX6455V7AORC6YGJJCUYVGSML/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:3RX6455V7AORC6YGJJCUYVGSML","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":"baa65533d1e2de9b591f71cf96f20f0969f44ae40ddee1a76285ffd0ac305870","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-05-14T17:35:27Z","title_canon_sha256":"ecfef00ec757544e3c5a38c59c5e1b2142ebbc9ac9a2c57f78b4a1495901966e"},"schema_version":"1.0","source":{"id":"2405.08786","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.08786","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"arxiv_version","alias_value":"2405.08786v2","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.08786","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"pith_short_12","alias_value":"3RX6455V7AOR","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"pith_short_16","alias_value":"3RX6455V7AORC6YG","created_at":"2026-07-05T08:42:04Z"},{"alias_kind":"pith_short_8","alias_value":"3RX6455V","created_at":"2026-07-05T08:42:04Z"}],"graph_snapshots":[{"event_id":"sha256:bb049dd4cc2251a622da2927000ffc2fbec1cf35551e9722c0de259c2c37e81e","target":"graph","created_at":"2026-07-05T08:42:04Z","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/2405.08786/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Prostate Imaging Reporting and Data System (PI-RADS) is pivotal in the diagnosis of clinically significant prostate cancer through MRI imaging. Current deep learning-based PI-RADS scoring methods often lack the incorporation of common PI-RADS clinical guideline~(PICG) utilized by radiologists, potentially compromising scoring accuracy. This paper introduces a novel approach that adapts a multi-modal large language model (MLLM) to incorporate PICG into PI-RADS scoring model without additional annotations and network parameters. We present a designed two-stage fine-tuning process aiming at a","authors_text":"Aasa Feragen, Hongda Guo, Ka Fung Peter Chiu, Manxi Lin, Qi Dou, Tiantian Zhang, Xiaofan Zhang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-05-14T17:35:27Z","title":"Incorporating Clinical Guidelines through Adapting Multi-modal Large Language Model for Prostate Cancer PI-RADS Scoring"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.08786","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:f4b8e45c866e17451e4937dc5a88afd55f3eab7b90ab72c5b3b64aca7a1f0bbc","target":"record","created_at":"2026-07-05T08:42:04Z","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":"baa65533d1e2de9b591f71cf96f20f0969f44ae40ddee1a76285ffd0ac305870","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-05-14T17:35:27Z","title_canon_sha256":"ecfef00ec757544e3c5a38c59c5e1b2142ebbc9ac9a2c57f78b4a1495901966e"},"schema_version":"1.0","source":{"id":"2405.08786","kind":"arxiv","version":2}},"canonical_sha256":"dc6fee77b5f81d117b064a454c54d262e037edb0b6f690357f882b5b97a42f20","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dc6fee77b5f81d117b064a454c54d262e037edb0b6f690357f882b5b97a42f20","first_computed_at":"2026-07-05T08:42:04.252106Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:42:04.252106Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bnkNHlL2ahZ27FDugFQYRyzSJmsUG4nLsA6NOjkPrhddwE8cMzRbnYcETNf5EhKPSkG5Dq828+VKwqkLtyNIDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:42:04.252592Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.08786","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f4b8e45c866e17451e4937dc5a88afd55f3eab7b90ab72c5b3b64aca7a1f0bbc","sha256:bb049dd4cc2251a622da2927000ffc2fbec1cf35551e9722c0de259c2c37e81e"],"state_sha256":"2413181f45ec37b45c014526b9f47011f7eae23c86301f647adeffc9bef68a32"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rW3ydLHUyohpblt3CTCVyqZdR30TuhJkSGlxZo4YEOvMiGJUDFXd37sSBpIxos5kZ1m24wpX7pgjrFXGgzwRAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T17:05:44.346323Z","bundle_sha256":"3b5de15edecf884c05d3e2947385e711dfa4f0d6bcb8bb2a6622e533004824e1"}}