{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:VDQ7CUWJE7PC7RICXOEBBWVBDG","short_pith_number":"pith:VDQ7CUWJ","canonical_record":{"source":{"id":"2606.05357","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-03T18:59:38Z","cross_cats_sorted":[],"title_canon_sha256":"1d1b259afe9a8a03adefd868099382e940fca30a65b8b573fc4baf7467e25cbf","abstract_canon_sha256":"0a2391717b7df940827b24d51eff667d8260c6f65a3887926f4524f26d6c4a8f"},"schema_version":"1.0"},"canonical_sha256":"a8e1f152c927de2fc502bb8810daa1199f5e41bbc76ddeca7ec0eeb5f2a54337","source":{"kind":"arxiv","id":"2606.05357","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05357","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05357v1","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05357","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"pith_short_12","alias_value":"VDQ7CUWJE7PC","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"pith_short_16","alias_value":"VDQ7CUWJE7PC7RIC","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"pith_short_8","alias_value":"VDQ7CUWJ","created_at":"2026-06-05T00:13:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:VDQ7CUWJE7PC7RICXOEBBWVBDG","target":"record","payload":{"canonical_record":{"source":{"id":"2606.05357","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-03T18:59:38Z","cross_cats_sorted":[],"title_canon_sha256":"1d1b259afe9a8a03adefd868099382e940fca30a65b8b573fc4baf7467e25cbf","abstract_canon_sha256":"0a2391717b7df940827b24d51eff667d8260c6f65a3887926f4524f26d6c4a8f"},"schema_version":"1.0"},"canonical_sha256":"a8e1f152c927de2fc502bb8810daa1199f5e41bbc76ddeca7ec0eeb5f2a54337","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T00:13:55.237179Z","signature_b64":"qkILcfpAGiTKbH7zgU8HyQaySyAlx5VG7eO1gnMsuZX9xG/8j+YvjEWWq3wMzkalhEdP42+ZiYIwtsEnXDfyBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a8e1f152c927de2fc502bb8810daa1199f5e41bbc76ddeca7ec0eeb5f2a54337","last_reissued_at":"2026-06-05T00:13:55.236704Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T00:13:55.236704Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.05357","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-05T00:13:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vlFVRt9OCMNeQ/rC7TqyMquvwLhiIMM5xXkOGfHLHDFIeaBtkedv74zyPq7WWV0/CUcu2giddsmPMSqGP2yyBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T11:35:34.237966Z"},"content_sha256":"4de44f1606231b30d25a38f74fcdfbf22d009f64e6311b95ba2a4751a27f3ad4","schema_version":"1.0","event_id":"sha256:4de44f1606231b30d25a38f74fcdfbf22d009f64e6311b95ba2a4751a27f3ad4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:VDQ7CUWJE7PC7RICXOEBBWVBDG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An interpretable and trustworthy AI framework for large-scale longitudinal structure-pain association studies using data from the Osteoarthritis Initiative (OAI)","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"C. Kent Kwoh, Haoyang Li, Hongxu Ding, Jincheng Yu, Rachel Yuanbao Chen, Shen Liu, Xiaoxiao Sun, Yiwen Liu","submitted_at":"2026-06-03T18:59:38Z","abstract_excerpt":"Purpose: To develop an interpretable and trustworthy AI framework that combines deep learning based MRI Osteoarthritis Knee Score (MOAKS) prediction with interpretable statistical modeling to study structure-pain relationships at scale using data from the Osteoarthritis Initiative (OAI). Materials and Methods: We first developed a deep learning framework to predict MOAKS features directly from knee MRIs and incorporated conformal prediction to provide prediction uncertainty quantification. This uncertainty-aware strategy enables explicit filtering of model outputs, retaining only high-confiden"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05357","kind":"arxiv","version":1},"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/2606.05357/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":"2026-06-05T00:13:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MQMEsPMsgy8hwbghQsnJafAOXt2fN4hYS0we3bfNcoOfELR9ry7/+PIfxtos/Eppbd4bpMnvI2sLAeeL6E9sCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T11:35:34.238347Z"},"content_sha256":"1767bb3c8792e5f9fbc5f46e9b45b73024a285a89148823e7d393633d6053898","schema_version":"1.0","event_id":"sha256:1767bb3c8792e5f9fbc5f46e9b45b73024a285a89148823e7d393633d6053898"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VDQ7CUWJE7PC7RICXOEBBWVBDG/bundle.json","state_url":"https://pith.science/pith/VDQ7CUWJE7PC7RICXOEBBWVBDG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VDQ7CUWJE7PC7RICXOEBBWVBDG/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":"2026-06-28T11:35:34Z","links":{"resolver":"https://pith.science/pith/VDQ7CUWJE7PC7RICXOEBBWVBDG","bundle":"https://pith.science/pith/VDQ7CUWJE7PC7RICXOEBBWVBDG/bundle.json","state":"https://pith.science/pith/VDQ7CUWJE7PC7RICXOEBBWVBDG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VDQ7CUWJE7PC7RICXOEBBWVBDG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:VDQ7CUWJE7PC7RICXOEBBWVBDG","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":"0a2391717b7df940827b24d51eff667d8260c6f65a3887926f4524f26d6c4a8f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-03T18:59:38Z","title_canon_sha256":"1d1b259afe9a8a03adefd868099382e940fca30a65b8b573fc4baf7467e25cbf"},"schema_version":"1.0","source":{"id":"2606.05357","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05357","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05357v1","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05357","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"pith_short_12","alias_value":"VDQ7CUWJE7PC","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"pith_short_16","alias_value":"VDQ7CUWJE7PC7RIC","created_at":"2026-06-05T00:13:55Z"},{"alias_kind":"pith_short_8","alias_value":"VDQ7CUWJ","created_at":"2026-06-05T00:13:55Z"}],"graph_snapshots":[{"event_id":"sha256:1767bb3c8792e5f9fbc5f46e9b45b73024a285a89148823e7d393633d6053898","target":"graph","created_at":"2026-06-05T00:13:55Z","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/2606.05357/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Purpose: To develop an interpretable and trustworthy AI framework that combines deep learning based MRI Osteoarthritis Knee Score (MOAKS) prediction with interpretable statistical modeling to study structure-pain relationships at scale using data from the Osteoarthritis Initiative (OAI). Materials and Methods: We first developed a deep learning framework to predict MOAKS features directly from knee MRIs and incorporated conformal prediction to provide prediction uncertainty quantification. This uncertainty-aware strategy enables explicit filtering of model outputs, retaining only high-confiden","authors_text":"C. Kent Kwoh, Haoyang Li, Hongxu Ding, Jincheng Yu, Rachel Yuanbao Chen, Shen Liu, Xiaoxiao Sun, Yiwen Liu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-03T18:59:38Z","title":"An interpretable and trustworthy AI framework for large-scale longitudinal structure-pain association studies using data from the Osteoarthritis Initiative (OAI)"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05357","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":"sha256:4de44f1606231b30d25a38f74fcdfbf22d009f64e6311b95ba2a4751a27f3ad4","target":"record","created_at":"2026-06-05T00:13:55Z","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":"0a2391717b7df940827b24d51eff667d8260c6f65a3887926f4524f26d6c4a8f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2026-06-03T18:59:38Z","title_canon_sha256":"1d1b259afe9a8a03adefd868099382e940fca30a65b8b573fc4baf7467e25cbf"},"schema_version":"1.0","source":{"id":"2606.05357","kind":"arxiv","version":1}},"canonical_sha256":"a8e1f152c927de2fc502bb8810daa1199f5e41bbc76ddeca7ec0eeb5f2a54337","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a8e1f152c927de2fc502bb8810daa1199f5e41bbc76ddeca7ec0eeb5f2a54337","first_computed_at":"2026-06-05T00:13:55.236704Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T00:13:55.236704Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qkILcfpAGiTKbH7zgU8HyQaySyAlx5VG7eO1gnMsuZX9xG/8j+YvjEWWq3wMzkalhEdP42+ZiYIwtsEnXDfyBQ==","signature_status":"signed_v1","signed_at":"2026-06-05T00:13:55.237179Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.05357","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4de44f1606231b30d25a38f74fcdfbf22d009f64e6311b95ba2a4751a27f3ad4","sha256:1767bb3c8792e5f9fbc5f46e9b45b73024a285a89148823e7d393633d6053898"],"state_sha256":"f9c4d6e23e4b97fe0874e51a4191b6a443ac3d1cc6849acfed766a245508a0a2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BjFRwiGutQui9yxFAXiM3sTkhBYFJa8GStL0+g/by6LQVlSZDa5NJ0sTgTx4zmSQNqnZwjpElcZwoZryGi4KAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T11:35:34.240273Z","bundle_sha256":"05f004642b2c4b1a6ba796598ab791db8bbf3ea09245acdd33b49b1a333aadb2"}}