{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:TRS4ZSHQBFNUYJ35RYTIPU6IDE","short_pith_number":"pith:TRS4ZSHQ","canonical_record":{"source":{"id":"1809.06993","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-19T03:16:26Z","cross_cats_sorted":[],"title_canon_sha256":"578d48be3d35f294982a0a38a2d34b1e4975269025972c6b3a8d2b3dcdeee2d3","abstract_canon_sha256":"707270cf83e6df2f71800e123b1da0ad2d798d2eab95b33905fec06e00183fb2"},"schema_version":"1.0"},"canonical_sha256":"9c65ccc8f0095b4c277d8e2687d3c819263e571e4a116433d7931ac5fba1b7fc","source":{"kind":"arxiv","id":"1809.06993","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06993","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06993v1","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06993","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"pith_short_12","alias_value":"TRS4ZSHQBFNU","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"TRS4ZSHQBFNUYJ35","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"TRS4ZSHQ","created_at":"2026-05-18T12:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:TRS4ZSHQBFNUYJ35RYTIPU6IDE","target":"record","payload":{"canonical_record":{"source":{"id":"1809.06993","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-19T03:16:26Z","cross_cats_sorted":[],"title_canon_sha256":"578d48be3d35f294982a0a38a2d34b1e4975269025972c6b3a8d2b3dcdeee2d3","abstract_canon_sha256":"707270cf83e6df2f71800e123b1da0ad2d798d2eab95b33905fec06e00183fb2"},"schema_version":"1.0"},"canonical_sha256":"9c65ccc8f0095b4c277d8e2687d3c819263e571e4a116433d7931ac5fba1b7fc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:05:20.961880Z","signature_b64":"VKIOL3CgvYl+HqJ8y63BtG7+G9DSQruGV3DUzU26Zmp2B1dy7Aa8S+IP0/MkfOo/jt5kSAyUAwLsz2TLzeVqAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c65ccc8f0095b4c277d8e2687d3c819263e571e4a116433d7931ac5fba1b7fc","last_reissued_at":"2026-05-18T00:05:20.961412Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:05:20.961412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.06993","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":"2026-05-18T00:05:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sYo2I97+S0CF/kX7+xKTuOxqHL7eHKPAgUhdaRlEFj16fGALiHVUvSw6IvWbYksIE7SnM5iXmC4IlvFrrTnGCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T03:18:51.112138Z"},"content_sha256":"e45783e23264b9ccf01ff76186152206e67a5a579bc89cce176afd7b5e0c32ea","schema_version":"1.0","event_id":"sha256:e45783e23264b9ccf01ff76186152206e67a5a579bc89cce176afd7b5e0c32ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:TRS4ZSHQBFNUYJ35RYTIPU6IDE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep-learning models improve on community-level diagnosis for common congenital heart disease lesions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Anita Moon-Grady, Erin Chinn, Lara Curran, Rima Arnaout, Yili Zhao","submitted_at":"2018-09-19T03:16:26Z","abstract_excerpt":"Prenatal diagnosis of tetralogy of Fallot (TOF) and hypoplastic left heart syndrome (HLHS), two serious congenital heart defects, improves outcomes and can in some cases facilitate in utero interventions. In practice, however, the fetal diagnosis rate for these lesions is only 30-50 percent in community settings. Improving fetal diagnosis of congenital heart disease is therefore critical. Deep learning is a cutting-edge machine learning technique for finding patterns in images but has not yet been applied to prenatal diagnosis of congenital heart disease. Using 685 retrospectively collected ec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06993","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":"2026-05-18T00:05:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xbl9HSMqj1RnoE5Nu5fAgfgs8XM8qnfR2omZu5e9ze8Xg2Kh+UiVpqGLg2zbyfTYdWBMgPcwil0y4TImZdhMDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-23T03:18:51.112501Z"},"content_sha256":"0643ddcf4cf588c176114448edd934f598ab8f71e1b7c363b65a432b3e131706","schema_version":"1.0","event_id":"sha256:0643ddcf4cf588c176114448edd934f598ab8f71e1b7c363b65a432b3e131706"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TRS4ZSHQBFNUYJ35RYTIPU6IDE/bundle.json","state_url":"https://pith.science/pith/TRS4ZSHQBFNUYJ35RYTIPU6IDE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TRS4ZSHQBFNUYJ35RYTIPU6IDE/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":"2026-06-23T03:18:51Z","links":{"resolver":"https://pith.science/pith/TRS4ZSHQBFNUYJ35RYTIPU6IDE","bundle":"https://pith.science/pith/TRS4ZSHQBFNUYJ35RYTIPU6IDE/bundle.json","state":"https://pith.science/pith/TRS4ZSHQBFNUYJ35RYTIPU6IDE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TRS4ZSHQBFNUYJ35RYTIPU6IDE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:TRS4ZSHQBFNUYJ35RYTIPU6IDE","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":"707270cf83e6df2f71800e123b1da0ad2d798d2eab95b33905fec06e00183fb2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-19T03:16:26Z","title_canon_sha256":"578d48be3d35f294982a0a38a2d34b1e4975269025972c6b3a8d2b3dcdeee2d3"},"schema_version":"1.0","source":{"id":"1809.06993","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.06993","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"arxiv_version","alias_value":"1809.06993v1","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.06993","created_at":"2026-05-18T00:05:20Z"},{"alias_kind":"pith_short_12","alias_value":"TRS4ZSHQBFNU","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"TRS4ZSHQBFNUYJ35","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"TRS4ZSHQ","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:0643ddcf4cf588c176114448edd934f598ab8f71e1b7c363b65a432b3e131706","target":"graph","created_at":"2026-05-18T00:05:20Z","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":"Prenatal diagnosis of tetralogy of Fallot (TOF) and hypoplastic left heart syndrome (HLHS), two serious congenital heart defects, improves outcomes and can in some cases facilitate in utero interventions. In practice, however, the fetal diagnosis rate for these lesions is only 30-50 percent in community settings. Improving fetal diagnosis of congenital heart disease is therefore critical. Deep learning is a cutting-edge machine learning technique for finding patterns in images but has not yet been applied to prenatal diagnosis of congenital heart disease. Using 685 retrospectively collected ec","authors_text":"Anita Moon-Grady, Erin Chinn, Lara Curran, Rima Arnaout, Yili Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-19T03:16:26Z","title":"Deep-learning models improve on community-level diagnosis for common congenital heart disease lesions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.06993","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:e45783e23264b9ccf01ff76186152206e67a5a579bc89cce176afd7b5e0c32ea","target":"record","created_at":"2026-05-18T00:05:20Z","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":"707270cf83e6df2f71800e123b1da0ad2d798d2eab95b33905fec06e00183fb2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-09-19T03:16:26Z","title_canon_sha256":"578d48be3d35f294982a0a38a2d34b1e4975269025972c6b3a8d2b3dcdeee2d3"},"schema_version":"1.0","source":{"id":"1809.06993","kind":"arxiv","version":1}},"canonical_sha256":"9c65ccc8f0095b4c277d8e2687d3c819263e571e4a116433d7931ac5fba1b7fc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c65ccc8f0095b4c277d8e2687d3c819263e571e4a116433d7931ac5fba1b7fc","first_computed_at":"2026-05-18T00:05:20.961412Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:05:20.961412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VKIOL3CgvYl+HqJ8y63BtG7+G9DSQruGV3DUzU26Zmp2B1dy7Aa8S+IP0/MkfOo/jt5kSAyUAwLsz2TLzeVqAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:05:20.961880Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.06993","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e45783e23264b9ccf01ff76186152206e67a5a579bc89cce176afd7b5e0c32ea","sha256:0643ddcf4cf588c176114448edd934f598ab8f71e1b7c363b65a432b3e131706"],"state_sha256":"a0a9e7e3f9f917263121acc20d717340ce882ba2db22926ca9d711097b2b6feb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pHNvvsJ5Tn/XccDw/pWlvL0mgN3WwH0z7Q+FVXNEwAesAO2DRkl6pNmRjJYMs+VjeP5zevfgBdINOz25Ki8gAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-23T03:18:51.114445Z","bundle_sha256":"48b95780f1b9d2783460da587fe21ecb5fdbd2649aa21101dcaac4568b797284"}}