{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PB5RWEEKFJHB6JUQDI7Q54FNWI","short_pith_number":"pith:PB5RWEEK","canonical_record":{"source":{"id":"2409.15834","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-24T08:03:13Z","cross_cats_sorted":[],"title_canon_sha256":"a389517d6344de141ec5d5d07a402a81a3bf81295705376ff33fc4b493b6c45e","abstract_canon_sha256":"c6dbdd18b002c7c0b1dbf8cdc82e75351eadb0c68dc2e5de40c4323aca49f40b"},"schema_version":"1.0"},"canonical_sha256":"787b1b108a2a4e1f26901a3f0ef0adb2379688919c72a760dc621b58eca968b8","source":{"kind":"arxiv","id":"2409.15834","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.15834","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"arxiv_version","alias_value":"2409.15834v1","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.15834","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_12","alias_value":"PB5RWEEKFJHB","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_16","alias_value":"PB5RWEEKFJHB6JUQ","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_8","alias_value":"PB5RWEEK","created_at":"2026-07-05T09:11:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PB5RWEEKFJHB6JUQDI7Q54FNWI","target":"record","payload":{"canonical_record":{"source":{"id":"2409.15834","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-24T08:03:13Z","cross_cats_sorted":[],"title_canon_sha256":"a389517d6344de141ec5d5d07a402a81a3bf81295705376ff33fc4b493b6c45e","abstract_canon_sha256":"c6dbdd18b002c7c0b1dbf8cdc82e75351eadb0c68dc2e5de40c4323aca49f40b"},"schema_version":"1.0"},"canonical_sha256":"787b1b108a2a4e1f26901a3f0ef0adb2379688919c72a760dc621b58eca968b8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:11:01.069978Z","signature_b64":"78xC8HTQCcT4CaWvOQItgqThLPYkc8qSzWrJdqW0zs0MTFr26EJfCY6Ql8Myt10DHht3l3X1QsPRH47jrGIbBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"787b1b108a2a4e1f26901a3f0ef0adb2379688919c72a760dc621b58eca968b8","last_reissued_at":"2026-07-05T09:11:01.069481Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:11:01.069481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.15834","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":"2026-07-05T09:11:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v4dgpyXrfjN+6i4IiNabrDBKFoPQm2YXP/MNYM+YKKB6vwwLWRyTE3Ay6xmYp4NFBxS2K0vbwGKipSGTBSRHDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T10:28:12.467487Z"},"content_sha256":"35cf269a4d656651e7bbf1821f57da65bf7bcdddd34b6e293d304fbfa0ab6ef5","schema_version":"1.0","event_id":"sha256:35cf269a4d656651e7bbf1821f57da65bf7bcdddd34b6e293d304fbfa0ab6ef5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PB5RWEEKFJHB6JUQDI7Q54FNWI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Learning Techniques for Automatic Lateral X-ray Cephalometric Landmark Detection: Is the Problem Solved?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bingsheng Huang, Chenglong Ma, Ching-Wei Wang, Dongqian Guo, Hikam Muzakky, Hongyuan Zhang, Hyunseok Lee, Juan Dai, Kunlun Xu, Pengfei He, Qian Wu, Xianan Cui, Xianlong Wang, Xuguang Li, Zhangnan Zhong, Zhu Zhu","submitted_at":"2024-09-24T08:03:13Z","abstract_excerpt":"Localization of the craniofacial landmarks from lateral cephalograms is a fundamental task in cephalometric analysis. The automation of the corresponding tasks has thus been the subject of intense research over the past decades. In this paper, we introduce the \"Cephalometric Landmark Detection (CL-Detection)\" dataset, which is the largest publicly available and comprehensive dataset for cephalometric landmark detection. This multi-center and multi-vendor dataset includes 600 lateral X-ray images with 38 landmarks acquired with different equipment from three medical centers. The overarching obj"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.15834","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/2409.15834/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":"2026-07-05T09:11:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zcYhYDC1MzKvEcSwDKQlYQUnOXxNHrvfKZF4yCdy9+O7o/hNFR0z4eEGeWt2nND1Qx2qanaHDOd8TaWNhrl/Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T10:28:12.467875Z"},"content_sha256":"cd0f4dc06749397afdb12e9a30d5da3c11c3c79adebf0d567152ba81f7864b79","schema_version":"1.0","event_id":"sha256:cd0f4dc06749397afdb12e9a30d5da3c11c3c79adebf0d567152ba81f7864b79"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PB5RWEEKFJHB6JUQDI7Q54FNWI/bundle.json","state_url":"https://pith.science/pith/PB5RWEEKFJHB6JUQDI7Q54FNWI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PB5RWEEKFJHB6JUQDI7Q54FNWI/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":"2026-07-14T10:28:12Z","links":{"resolver":"https://pith.science/pith/PB5RWEEKFJHB6JUQDI7Q54FNWI","bundle":"https://pith.science/pith/PB5RWEEKFJHB6JUQDI7Q54FNWI/bundle.json","state":"https://pith.science/pith/PB5RWEEKFJHB6JUQDI7Q54FNWI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PB5RWEEKFJHB6JUQDI7Q54FNWI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PB5RWEEKFJHB6JUQDI7Q54FNWI","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":"c6dbdd18b002c7c0b1dbf8cdc82e75351eadb0c68dc2e5de40c4323aca49f40b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-24T08:03:13Z","title_canon_sha256":"a389517d6344de141ec5d5d07a402a81a3bf81295705376ff33fc4b493b6c45e"},"schema_version":"1.0","source":{"id":"2409.15834","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.15834","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"arxiv_version","alias_value":"2409.15834v1","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.15834","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_12","alias_value":"PB5RWEEKFJHB","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_16","alias_value":"PB5RWEEKFJHB6JUQ","created_at":"2026-07-05T09:11:01Z"},{"alias_kind":"pith_short_8","alias_value":"PB5RWEEK","created_at":"2026-07-05T09:11:01Z"}],"graph_snapshots":[{"event_id":"sha256:cd0f4dc06749397afdb12e9a30d5da3c11c3c79adebf0d567152ba81f7864b79","target":"graph","created_at":"2026-07-05T09:11:01Z","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/2409.15834/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Localization of the craniofacial landmarks from lateral cephalograms is a fundamental task in cephalometric analysis. The automation of the corresponding tasks has thus been the subject of intense research over the past decades. In this paper, we introduce the \"Cephalometric Landmark Detection (CL-Detection)\" dataset, which is the largest publicly available and comprehensive dataset for cephalometric landmark detection. This multi-center and multi-vendor dataset includes 600 lateral X-ray images with 38 landmarks acquired with different equipment from three medical centers. The overarching obj","authors_text":"Bingsheng Huang, Chenglong Ma, Ching-Wei Wang, Dongqian Guo, Hikam Muzakky, Hongyuan Zhang, Hyunseok Lee, Juan Dai, Kunlun Xu, Pengfei He, Qian Wu, Xianan Cui, Xianlong Wang, Xuguang Li, Zhangnan Zhong, Zhu Zhu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-24T08:03:13Z","title":"Deep Learning Techniques for Automatic Lateral X-ray Cephalometric Landmark Detection: Is the Problem Solved?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.15834","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":"sha256:35cf269a4d656651e7bbf1821f57da65bf7bcdddd34b6e293d304fbfa0ab6ef5","target":"record","created_at":"2026-07-05T09:11:01Z","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":"c6dbdd18b002c7c0b1dbf8cdc82e75351eadb0c68dc2e5de40c4323aca49f40b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-24T08:03:13Z","title_canon_sha256":"a389517d6344de141ec5d5d07a402a81a3bf81295705376ff33fc4b493b6c45e"},"schema_version":"1.0","source":{"id":"2409.15834","kind":"arxiv","version":1}},"canonical_sha256":"787b1b108a2a4e1f26901a3f0ef0adb2379688919c72a760dc621b58eca968b8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"787b1b108a2a4e1f26901a3f0ef0adb2379688919c72a760dc621b58eca968b8","first_computed_at":"2026-07-05T09:11:01.069481Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:11:01.069481Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"78xC8HTQCcT4CaWvOQItgqThLPYkc8qSzWrJdqW0zs0MTFr26EJfCY6Ql8Myt10DHht3l3X1QsPRH47jrGIbBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:11:01.069978Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.15834","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:35cf269a4d656651e7bbf1821f57da65bf7bcdddd34b6e293d304fbfa0ab6ef5","sha256:cd0f4dc06749397afdb12e9a30d5da3c11c3c79adebf0d567152ba81f7864b79"],"state_sha256":"70346046d5f69831f3c91618cf84de5c52d27678956a92d5cdd118622bad7bf8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XHHojb6i6K5JBNlOQiMevMsDwM8Yp6LNI+gkJK5ioQ9MI3dXd84CXx2vAInVV2/mbrCaUNu2Tct0kNukKtA6Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-14T10:28:12.470017Z","bundle_sha256":"a86c648b751a33678f2183f5d46e354987a2a459d280b8fbe0b441d8d952b03f"}}