{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:4PZWVU7J7WZQSTMBH7EOUKOGLY","short_pith_number":"pith:4PZWVU7J","canonical_record":{"source":{"id":"1906.09354","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T23:55:36Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"2dbbb19c3a9cea071cabb6b98cea037496b42ee82edda80b913272a76b5638ce","abstract_canon_sha256":"44dbe836cb7b5ccf60bd74f22378200b67725bf0d1f405df16e8140d51ea4594"},"schema_version":"1.0"},"canonical_sha256":"e3f36ad3e9fdb3094d813fc8ea29c65e0656aaab3c15f3ddf3febdb3d5ab4907","source":{"kind":"arxiv","id":"1906.09354","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.09354","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"arxiv_version","alias_value":"1906.09354v1","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.09354","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"pith_short_12","alias_value":"4PZWVU7J7WZQ","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4PZWVU7J7WZQSTMB","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4PZWVU7J","created_at":"2026-05-18T12:33:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:4PZWVU7J7WZQSTMBH7EOUKOGLY","target":"record","payload":{"canonical_record":{"source":{"id":"1906.09354","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T23:55:36Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"2dbbb19c3a9cea071cabb6b98cea037496b42ee82edda80b913272a76b5638ce","abstract_canon_sha256":"44dbe836cb7b5ccf60bd74f22378200b67725bf0d1f405df16e8140d51ea4594"},"schema_version":"1.0"},"canonical_sha256":"e3f36ad3e9fdb3094d813fc8ea29c65e0656aaab3c15f3ddf3febdb3d5ab4907","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:38.389814Z","signature_b64":"FYOZKZ4Ixj5VAcdGzxaW4RyWZcRMstGYXqZqJcvgTD3FvLExEgMPSUTpICPgqamqVlEFgr+mCAeJQQ7rSky0Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e3f36ad3e9fdb3094d813fc8ea29c65e0656aaab3c15f3ddf3febdb3d5ab4907","last_reissued_at":"2026-05-17T23:42:38.389141Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:38.389141Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.09354","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":"2026-05-17T23:42:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Gl7n13Uvh6ptm6oaO2coho8aV90ktw0bTdGXsMx7anoKRI3h+t/It4s4DskdAwoW9uMWnJob1R2CyPhRrimzBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T19:13:12.616450Z"},"content_sha256":"ac5e0435b90659d1cbe568172b74ed5e6618d25923f53f4d2a7383190286337b","schema_version":"1.0","event_id":"sha256:ac5e0435b90659d1cbe568172b74ed5e6618d25923f53f4d2a7383190286337b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:4PZWVU7J7WZQSTMBH7EOUKOGLY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Boosting the rule-out accuracy of deep disease detection using class weight modifiers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"eess.IV","authors_text":"Alexandros Karargyris, Joy T. Wu, Ken C. L. Wong, Mehdi Moradi, Tanveer Syeda-Mahmood","submitted_at":"2019-06-21T23:55:36Z","abstract_excerpt":"In many screening applications, the primary goal of a radiologist or assisting artificial intelligence is to rule out certain findings. The classifiers built for such applications are often trained on large datasets that derive labels from clinical notes written for patients. While the quality of the positive findings described in these notes is often reliable, lack of the mention of a finding does not always rule out the presence of it. This happens because radiologists comment on the patient in the context of the exam, for example focusing on trauma as opposed to chronic disease at emergency"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.09354","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":""},"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":"2026-05-17T23:42:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5+q3V1DFovBHsK93paTwLfOUof5IWQfehLN+hYJF46xzHN4DavUlEnZfr3ByKAcZA+X4XLjjjDzLIUfioOAoBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T19:13:12.616850Z"},"content_sha256":"2ebc870487123a33c746cb24cf164fa78901e747eba5d21947034321af7b8bab","schema_version":"1.0","event_id":"sha256:2ebc870487123a33c746cb24cf164fa78901e747eba5d21947034321af7b8bab"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4PZWVU7J7WZQSTMBH7EOUKOGLY/bundle.json","state_url":"https://pith.science/pith/4PZWVU7J7WZQSTMBH7EOUKOGLY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4PZWVU7J7WZQSTMBH7EOUKOGLY/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":"2026-05-26T19:13:12Z","links":{"resolver":"https://pith.science/pith/4PZWVU7J7WZQSTMBH7EOUKOGLY","bundle":"https://pith.science/pith/4PZWVU7J7WZQSTMBH7EOUKOGLY/bundle.json","state":"https://pith.science/pith/4PZWVU7J7WZQSTMBH7EOUKOGLY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4PZWVU7J7WZQSTMBH7EOUKOGLY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:4PZWVU7J7WZQSTMBH7EOUKOGLY","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":"44dbe836cb7b5ccf60bd74f22378200b67725bf0d1f405df16e8140d51ea4594","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T23:55:36Z","title_canon_sha256":"2dbbb19c3a9cea071cabb6b98cea037496b42ee82edda80b913272a76b5638ce"},"schema_version":"1.0","source":{"id":"1906.09354","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.09354","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"arxiv_version","alias_value":"1906.09354v1","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.09354","created_at":"2026-05-17T23:42:38Z"},{"alias_kind":"pith_short_12","alias_value":"4PZWVU7J7WZQ","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"4PZWVU7J7WZQSTMB","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"4PZWVU7J","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:2ebc870487123a33c746cb24cf164fa78901e747eba5d21947034321af7b8bab","target":"graph","created_at":"2026-05-17T23:42:38Z","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"},"paper":{"abstract_excerpt":"In many screening applications, the primary goal of a radiologist or assisting artificial intelligence is to rule out certain findings. The classifiers built for such applications are often trained on large datasets that derive labels from clinical notes written for patients. While the quality of the positive findings described in these notes is often reliable, lack of the mention of a finding does not always rule out the presence of it. This happens because radiologists comment on the patient in the context of the exam, for example focusing on trauma as opposed to chronic disease at emergency","authors_text":"Alexandros Karargyris, Joy T. Wu, Ken C. L. Wong, Mehdi Moradi, Tanveer Syeda-Mahmood","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T23:55:36Z","title":"Boosting the rule-out accuracy of deep disease detection using class weight modifiers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.09354","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:ac5e0435b90659d1cbe568172b74ed5e6618d25923f53f4d2a7383190286337b","target":"record","created_at":"2026-05-17T23:42:38Z","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":"44dbe836cb7b5ccf60bd74f22378200b67725bf0d1f405df16e8140d51ea4594","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2019-06-21T23:55:36Z","title_canon_sha256":"2dbbb19c3a9cea071cabb6b98cea037496b42ee82edda80b913272a76b5638ce"},"schema_version":"1.0","source":{"id":"1906.09354","kind":"arxiv","version":1}},"canonical_sha256":"e3f36ad3e9fdb3094d813fc8ea29c65e0656aaab3c15f3ddf3febdb3d5ab4907","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e3f36ad3e9fdb3094d813fc8ea29c65e0656aaab3c15f3ddf3febdb3d5ab4907","first_computed_at":"2026-05-17T23:42:38.389141Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:38.389141Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FYOZKZ4Ixj5VAcdGzxaW4RyWZcRMstGYXqZqJcvgTD3FvLExEgMPSUTpICPgqamqVlEFgr+mCAeJQQ7rSky0Aw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:38.389814Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.09354","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac5e0435b90659d1cbe568172b74ed5e6618d25923f53f4d2a7383190286337b","sha256:2ebc870487123a33c746cb24cf164fa78901e747eba5d21947034321af7b8bab"],"state_sha256":"20268582fdc1b3831d130a499a628a7c718fb8704cfbed57d019a6efa2e7ed73"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yiA2W+KO0s8s6ZBaWaWGqWJ4DLIQJADJlRnY1cpnhK3JmoHbp0SbEgDOhfKaLuyInex2CNbOtunUB69uoIYNDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T19:13:12.619054Z","bundle_sha256":"3be15d85c35c81466968457d3cb2fb97c372aa26a16db3a200428f2e89d59859"}}