{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:LA2XBRBPPJBBSEVFWVBLV4GKL3","short_pith_number":"pith:LA2XBRBP","canonical_record":{"source":{"id":"2202.01975","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2022-02-02T15:15:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ae34252c032a0d74616c45fe9e4dad3f4de426b897adb17ce67b9ad4a917f08b","abstract_canon_sha256":"cd3b97f3ad082f9d855fea360b5859edda30151b5e8508080a58296bab1a4f60"},"schema_version":"1.0"},"canonical_sha256":"583570c42f7a421912a5b542baf0ca5efde20a58cf678ce3861ddffafe04f173","source":{"kind":"arxiv","id":"2202.01975","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.01975","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"arxiv_version","alias_value":"2202.01975v1","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.01975","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"pith_short_12","alias_value":"LA2XBRBPPJBB","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"pith_short_16","alias_value":"LA2XBRBPPJBBSEVF","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"pith_short_8","alias_value":"LA2XBRBP","created_at":"2026-07-05T03:54:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:LA2XBRBPPJBBSEVFWVBLV4GKL3","target":"record","payload":{"canonical_record":{"source":{"id":"2202.01975","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2022-02-02T15:15:03Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"ae34252c032a0d74616c45fe9e4dad3f4de426b897adb17ce67b9ad4a917f08b","abstract_canon_sha256":"cd3b97f3ad082f9d855fea360b5859edda30151b5e8508080a58296bab1a4f60"},"schema_version":"1.0"},"canonical_sha256":"583570c42f7a421912a5b542baf0ca5efde20a58cf678ce3861ddffafe04f173","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:54:07.640185Z","signature_b64":"9aj874SWhWhvjvF25ZOQgPu0pERYEOkvPi7TtURS9O8AySqDKwHAiXVQFXkC+vIcmb1Lzj0atfjhVTGoPkOVDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"583570c42f7a421912a5b542baf0ca5efde20a58cf678ce3861ddffafe04f173","last_reissued_at":"2026-07-05T03:54:07.639709Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:54:07.639709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2202.01975","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":"2026-07-05T03:54:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IDKWCSku2hCr0Cn/KUyJckN63VuGi0c84KpRIKMbaIJzLYZc3yQHPIUhliQzBfRUA32Rlr22PW/c21otXfBXCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T14:42:45.673186Z"},"content_sha256":"e52e4f6b1887d5f197de4d6a9f10b10e91fa8d7024704c293139f0492ecabb25","schema_version":"1.0","event_id":"sha256:e52e4f6b1887d5f197de4d6a9f10b10e91fa8d7024704c293139f0492ecabb25"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:LA2XBRBPPJBBSEVFWVBLV4GKL3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Performance of multilabel machine learning models and risk stratification schemas for predicting stroke and bleeding risk in patients with non-valvular atrial fibrillation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"q-bio.QM","authors_text":"Benjamin Chow, Brendan McQuillan, Ferdous Sohel, Frank Sanfilippo, Girish Dwivedi, Jonathon Stewart, Joseph Hung, Juan lu, Kevin Murray, Mohammed Bennamoun, Rebecca Hutchens, Tom Briffa","submitted_at":"2022-02-02T15:15:03Z","abstract_excerpt":"Appropriate antithrombotic therapy for patients with atrial fibrillation (AF) requires assessment of ischemic stroke and bleeding risks. However, risk stratification schemas such as CHA2DS2-VASc and HAS-BLED have modest predictive capacity for patients with AF. Machine learning (ML) techniques may improve predictive performance and support decision-making for appropriate antithrombotic therapy. We compared the performance of multilabel ML models with the currently used risk scores for predicting outcomes in AF patients. Materials and Methods This was a retrospective cohort study of 9670 patien"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.01975","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/2202.01975/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":"2026-07-05T03:54:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"84PbzXanMvkTyeNly1rEEWBs83XKNN/Aq3qUB7Av8Gn4P2TfsbEiJpOieSbIy5zXrVvrkJqpOhWgx3nvQGgmBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T14:42:45.673842Z"},"content_sha256":"93f968a963640831953d3e0cf44404a7b1f19917e18d7ecc00d04dafc918f5ff","schema_version":"1.0","event_id":"sha256:93f968a963640831953d3e0cf44404a7b1f19917e18d7ecc00d04dafc918f5ff"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LA2XBRBPPJBBSEVFWVBLV4GKL3/bundle.json","state_url":"https://pith.science/pith/LA2XBRBPPJBBSEVFWVBLV4GKL3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LA2XBRBPPJBBSEVFWVBLV4GKL3/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":"2026-07-05T14:42:45Z","links":{"resolver":"https://pith.science/pith/LA2XBRBPPJBBSEVFWVBLV4GKL3","bundle":"https://pith.science/pith/LA2XBRBPPJBBSEVFWVBLV4GKL3/bundle.json","state":"https://pith.science/pith/LA2XBRBPPJBBSEVFWVBLV4GKL3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LA2XBRBPPJBBSEVFWVBLV4GKL3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LA2XBRBPPJBBSEVFWVBLV4GKL3","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":"cd3b97f3ad082f9d855fea360b5859edda30151b5e8508080a58296bab1a4f60","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2022-02-02T15:15:03Z","title_canon_sha256":"ae34252c032a0d74616c45fe9e4dad3f4de426b897adb17ce67b9ad4a917f08b"},"schema_version":"1.0","source":{"id":"2202.01975","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2202.01975","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"arxiv_version","alias_value":"2202.01975v1","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2202.01975","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"pith_short_12","alias_value":"LA2XBRBPPJBB","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"pith_short_16","alias_value":"LA2XBRBPPJBBSEVF","created_at":"2026-07-05T03:54:07Z"},{"alias_kind":"pith_short_8","alias_value":"LA2XBRBP","created_at":"2026-07-05T03:54:07Z"}],"graph_snapshots":[{"event_id":"sha256:93f968a963640831953d3e0cf44404a7b1f19917e18d7ecc00d04dafc918f5ff","target":"graph","created_at":"2026-07-05T03:54:07Z","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/2202.01975/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Appropriate antithrombotic therapy for patients with atrial fibrillation (AF) requires assessment of ischemic stroke and bleeding risks. However, risk stratification schemas such as CHA2DS2-VASc and HAS-BLED have modest predictive capacity for patients with AF. Machine learning (ML) techniques may improve predictive performance and support decision-making for appropriate antithrombotic therapy. We compared the performance of multilabel ML models with the currently used risk scores for predicting outcomes in AF patients. Materials and Methods This was a retrospective cohort study of 9670 patien","authors_text":"Benjamin Chow, Brendan McQuillan, Ferdous Sohel, Frank Sanfilippo, Girish Dwivedi, Jonathon Stewart, Joseph Hung, Juan lu, Kevin Murray, Mohammed Bennamoun, Rebecca Hutchens, Tom Briffa","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2022-02-02T15:15:03Z","title":"Performance of multilabel machine learning models and risk stratification schemas for predicting stroke and bleeding risk in patients with non-valvular atrial fibrillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2202.01975","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:e52e4f6b1887d5f197de4d6a9f10b10e91fa8d7024704c293139f0492ecabb25","target":"record","created_at":"2026-07-05T03:54:07Z","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":"cd3b97f3ad082f9d855fea360b5859edda30151b5e8508080a58296bab1a4f60","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.QM","submitted_at":"2022-02-02T15:15:03Z","title_canon_sha256":"ae34252c032a0d74616c45fe9e4dad3f4de426b897adb17ce67b9ad4a917f08b"},"schema_version":"1.0","source":{"id":"2202.01975","kind":"arxiv","version":1}},"canonical_sha256":"583570c42f7a421912a5b542baf0ca5efde20a58cf678ce3861ddffafe04f173","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"583570c42f7a421912a5b542baf0ca5efde20a58cf678ce3861ddffafe04f173","first_computed_at":"2026-07-05T03:54:07.639709Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:54:07.639709Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9aj874SWhWhvjvF25ZOQgPu0pERYEOkvPi7TtURS9O8AySqDKwHAiXVQFXkC+vIcmb1Lzj0atfjhVTGoPkOVDw==","signature_status":"signed_v1","signed_at":"2026-07-05T03:54:07.640185Z","signed_message":"canonical_sha256_bytes"},"source_id":"2202.01975","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e52e4f6b1887d5f197de4d6a9f10b10e91fa8d7024704c293139f0492ecabb25","sha256:93f968a963640831953d3e0cf44404a7b1f19917e18d7ecc00d04dafc918f5ff"],"state_sha256":"8f641f42dadd30537215485f3ae96641082dfa323e35c7a88a549e35610765bb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Hv6+EbchSRqJnF5wcvcNryUpn8WQ0VH6lBLHr8ely2JZY+GuuOS4mjM4okSe98LE15vpMrwA+WyBhBd1LqKXAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T14:42:45.678199Z","bundle_sha256":"3fa228eb5d1096a7767d501b71a318975bdb956333f82bf18f51f39f8b667048"}}