{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HLLSKEY2K6C2M34JYJXHF2U25K","short_pith_number":"pith:HLLSKEY2","canonical_record":{"source":{"id":"1801.07637","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-23T16:18:24Z","cross_cats_sorted":[],"title_canon_sha256":"71df0454e27e58db27a2ea5c9050c7969b2c377c1f48d9435bead7213515179b","abstract_canon_sha256":"4f4f301724438627499ea5156dfb9b294a8411c2d814ba1dad9336e5411c8644"},"schema_version":"1.0"},"canonical_sha256":"3ad725131a5785a66f89c26e72ea9aeab8c09205aca6389d4b66c8e2b7efaa57","source":{"kind":"arxiv","id":"1801.07637","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.07637","created_at":"2026-05-18T00:25:12Z"},{"alias_kind":"arxiv_version","alias_value":"1801.07637v1","created_at":"2026-05-18T00:25:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.07637","created_at":"2026-05-18T00:25:12Z"},{"alias_kind":"pith_short_12","alias_value":"HLLSKEY2K6C2","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HLLSKEY2K6C2M34J","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HLLSKEY2","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HLLSKEY2K6C2M34JYJXHF2U25K","target":"record","payload":{"canonical_record":{"source":{"id":"1801.07637","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-23T16:18:24Z","cross_cats_sorted":[],"title_canon_sha256":"71df0454e27e58db27a2ea5c9050c7969b2c377c1f48d9435bead7213515179b","abstract_canon_sha256":"4f4f301724438627499ea5156dfb9b294a8411c2d814ba1dad9336e5411c8644"},"schema_version":"1.0"},"canonical_sha256":"3ad725131a5785a66f89c26e72ea9aeab8c09205aca6389d4b66c8e2b7efaa57","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:25:12.375530Z","signature_b64":"Sm5/8oDJZJeuhfL5U0h+nQ5ZMA4nMCC3mQ2mpIKaM3IViVC1wpWFCJbtc+Vjh+LoPg0HZPc6PPOSLaw5BC1YAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3ad725131a5785a66f89c26e72ea9aeab8c09205aca6389d4b66c8e2b7efaa57","last_reissued_at":"2026-05-18T00:25:12.375049Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:25:12.375049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1801.07637","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":"2026-05-18T00:25:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GbDsEeq56kTClbzRvlVyyWHuyLpPvm5RdOKJvdWOM4iK3RfhwkPB+sxkjzUVgaYUK0aaIue6iECdIWCqauK6Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T05:32:26.306310Z"},"content_sha256":"6c8bbc96e81fcc9967043086ec9d7e5af28199c6ee5ac892a6be4df725bef441","schema_version":"1.0","event_id":"sha256:6c8bbc96e81fcc9967043086ec9d7e5af28199c6ee5ac892a6be4df725bef441"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HLLSKEY2K6C2M34JYJXHF2U25K","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepGestalt - Identifying Rare Genetic Syndromes Using Deep Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dekel Gelbman, Karen W. Gripp, Lina Basel-Salmon, Lynne M. Bird, Martin Zenker, Nicole Fleischer, Omri Bar, Peter Krawitz, Susanne B Kamphausen, Yair Hanani, Yaron Gurovich","submitted_at":"2018-01-23T16:18:24Z","abstract_excerpt":"Facial analysis technologies have recently measured up to the capabilities of expert clinicians in syndrome identification. To date, these technologies could only identify phenotypes of a few diseases, limiting their role in clinical settings where hundreds of diagnoses must be considered.\n  We developed a facial analysis framework, DeepGestalt, using computer vision and deep learning algorithms, that quantifies similarities to hundreds of genetic syndromes based on unconstrained 2D images. DeepGestalt is currently trained with over 26,000 patient cases from a rapidly growing phenotype-genotyp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.07637","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":"2026-05-18T00:25:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OBO1RZnWxtGp872BID9wHUMXTJEXGTZhSsa4IGrax96A2qNWnYU99a7GMh7Pns4ZZ9YIKdhULamiOVHmd2yZCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-25T05:32:26.306682Z"},"content_sha256":"19c70fb404295c2e1e3b241fc66561aeb67e760e8132efe89e3adad9db3425e1","schema_version":"1.0","event_id":"sha256:19c70fb404295c2e1e3b241fc66561aeb67e760e8132efe89e3adad9db3425e1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HLLSKEY2K6C2M34JYJXHF2U25K/bundle.json","state_url":"https://pith.science/pith/HLLSKEY2K6C2M34JYJXHF2U25K/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HLLSKEY2K6C2M34JYJXHF2U25K/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":"2026-06-25T05:32:26Z","links":{"resolver":"https://pith.science/pith/HLLSKEY2K6C2M34JYJXHF2U25K","bundle":"https://pith.science/pith/HLLSKEY2K6C2M34JYJXHF2U25K/bundle.json","state":"https://pith.science/pith/HLLSKEY2K6C2M34JYJXHF2U25K/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HLLSKEY2K6C2M34JYJXHF2U25K/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HLLSKEY2K6C2M34JYJXHF2U25K","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":"4f4f301724438627499ea5156dfb9b294a8411c2d814ba1dad9336e5411c8644","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-23T16:18:24Z","title_canon_sha256":"71df0454e27e58db27a2ea5c9050c7969b2c377c1f48d9435bead7213515179b"},"schema_version":"1.0","source":{"id":"1801.07637","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.07637","created_at":"2026-05-18T00:25:12Z"},{"alias_kind":"arxiv_version","alias_value":"1801.07637v1","created_at":"2026-05-18T00:25:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.07637","created_at":"2026-05-18T00:25:12Z"},{"alias_kind":"pith_short_12","alias_value":"HLLSKEY2K6C2","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HLLSKEY2K6C2M34J","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HLLSKEY2","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:19c70fb404295c2e1e3b241fc66561aeb67e760e8132efe89e3adad9db3425e1","target":"graph","created_at":"2026-05-18T00:25:12Z","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":"Facial analysis technologies have recently measured up to the capabilities of expert clinicians in syndrome identification. To date, these technologies could only identify phenotypes of a few diseases, limiting their role in clinical settings where hundreds of diagnoses must be considered.\n  We developed a facial analysis framework, DeepGestalt, using computer vision and deep learning algorithms, that quantifies similarities to hundreds of genetic syndromes based on unconstrained 2D images. DeepGestalt is currently trained with over 26,000 patient cases from a rapidly growing phenotype-genotyp","authors_text":"Dekel Gelbman, Karen W. Gripp, Lina Basel-Salmon, Lynne M. Bird, Martin Zenker, Nicole Fleischer, Omri Bar, Peter Krawitz, Susanne B Kamphausen, Yair Hanani, Yaron Gurovich","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-23T16:18:24Z","title":"DeepGestalt - Identifying Rare Genetic Syndromes Using Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.07637","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":"sha256:6c8bbc96e81fcc9967043086ec9d7e5af28199c6ee5ac892a6be4df725bef441","target":"record","created_at":"2026-05-18T00:25:12Z","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":"4f4f301724438627499ea5156dfb9b294a8411c2d814ba1dad9336e5411c8644","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-23T16:18:24Z","title_canon_sha256":"71df0454e27e58db27a2ea5c9050c7969b2c377c1f48d9435bead7213515179b"},"schema_version":"1.0","source":{"id":"1801.07637","kind":"arxiv","version":1}},"canonical_sha256":"3ad725131a5785a66f89c26e72ea9aeab8c09205aca6389d4b66c8e2b7efaa57","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3ad725131a5785a66f89c26e72ea9aeab8c09205aca6389d4b66c8e2b7efaa57","first_computed_at":"2026-05-18T00:25:12.375049Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:25:12.375049Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Sm5/8oDJZJeuhfL5U0h+nQ5ZMA4nMCC3mQ2mpIKaM3IViVC1wpWFCJbtc+Vjh+LoPg0HZPc6PPOSLaw5BC1YAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:25:12.375530Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.07637","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6c8bbc96e81fcc9967043086ec9d7e5af28199c6ee5ac892a6be4df725bef441","sha256:19c70fb404295c2e1e3b241fc66561aeb67e760e8132efe89e3adad9db3425e1"],"state_sha256":"b0e769b3610bf9ffe86047e36f1b2521da8e0148a01a5b22ef1ffb71e435f4f9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PHgLLFoYQ0itAtn3GuA7CL0NONPW9bF/CWwyoU1+gG+Mjet//5+G3gGHa1Ons8oILYYTIE22g7b+dNA3xNw4Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-25T05:32:26.308618Z","bundle_sha256":"8c1b117ffc96a35c75526ec5d95b516ddaef7d7a74dd678a72a732f999d35ed0"}}