{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:SYFY3NEEATD7RQ4TL6DNUKNCLD","short_pith_number":"pith:SYFY3NEE","canonical_record":{"source":{"id":"2607.19600","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-21T22:04:17Z","cross_cats_sorted":["cs.CV","cs.LG","q-bio.QM","stat.ML"],"title_canon_sha256":"1e1dfab892ca079cae864460cb0c8d0204d6a7dfa5efe8539a24b72acbe3ca2b","abstract_canon_sha256":"9693060eae6b76641e69ad1653a661ebc4b0ce61c05f0bffae4a282fd6928380"},"schema_version":"1.0"},"canonical_sha256":"960b8db48404c7f8c3935f86da29a258d996d64cf8bab10bd4e4fc85d64401bb","source":{"kind":"arxiv","id":"2607.19600","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.19600","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"arxiv_version","alias_value":"2607.19600v1","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.19600","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"pith_short_12","alias_value":"SYFY3NEEATD7","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"pith_short_16","alias_value":"SYFY3NEEATD7RQ4T","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"pith_short_8","alias_value":"SYFY3NEE","created_at":"2026-07-23T00:23:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:SYFY3NEEATD7RQ4TL6DNUKNCLD","target":"record","payload":{"canonical_record":{"source":{"id":"2607.19600","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-21T22:04:17Z","cross_cats_sorted":["cs.CV","cs.LG","q-bio.QM","stat.ML"],"title_canon_sha256":"1e1dfab892ca079cae864460cb0c8d0204d6a7dfa5efe8539a24b72acbe3ca2b","abstract_canon_sha256":"9693060eae6b76641e69ad1653a661ebc4b0ce61c05f0bffae4a282fd6928380"},"schema_version":"1.0"},"canonical_sha256":"960b8db48404c7f8c3935f86da29a258d996d64cf8bab10bd4e4fc85d64401bb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-23T00:23:58.708993Z","signature_b64":"AST5trT/KK01x40Z8+aMca6NEp8+94SyhQgiKQFd0gD30/EvwicN+Rc0XkcqQDXMPPGx7YBUCbAa1ZGmbujjCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"960b8db48404c7f8c3935f86da29a258d996d64cf8bab10bd4e4fc85d64401bb","last_reissued_at":"2026-07-23T00:23:58.708132Z","signature_status":"signed_v1","first_computed_at":"2026-07-23T00:23:58.708132Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.19600","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":"2026-07-23T00:23:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SMCqJN4mxnNlCamkCbiMIS4xbLEzVduBObJqZOr9RV/LpRcioHRXG8i1taH+ZSrURovAYoxOU6aC2pdfdm1WBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T07:41:49.367680Z"},"content_sha256":"b374261df766aed6b3b4026d47d1bbfa2cce84eaf1026f36b1d71b8f619ad511","schema_version":"1.0","event_id":"sha256:b374261df766aed6b3b4026d47d1bbfa2cce84eaf1026f36b1d71b8f619ad511"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:SYFY3NEEATD7RQ4TL6DNUKNCLD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Shape Regression for Planar Curves with Multimodal Covariates","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG","q-bio.QM","stat.ML"],"primary_cat":"stat.ME","authors_text":"Hadya Yassin, Kerstin Ritter, Manuel Pfeuffer, Roshan Prakash Rane, Sonja Greven","submitted_at":"2026-07-21T22:04:17Z","abstract_excerpt":"The shape of a planar curve is the geometric information that remains once translation, rotation, scale and reparametrisation are removed and is of interest in many health applications, e.g. in neuroimaging. We propose a deep shape regression model for open planar curves that admits multimodal and high-dimensional covariates. Representing curves as complex-valued functions, we show that the conditional full Procrustes mean is the leading eigenfunction of the conditional covariance. To estimate this covariance surface, we propose a novel deep conditional covariance smoother with modality-specif"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.19600","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/2607.19600/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":"2026-07-23T00:23:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UaHebre9WLShl70/LqQMe/mBTl5uEfxBmMipx4QHQD7MeH6yvpE5S3Weixjb7PNtsD+WBg15l9Be3sAGSlwjBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T07:41:49.368223Z"},"content_sha256":"b95944266132ddf9fe63b156eddfb156b6117238c34469375a0569ee5248e75d","schema_version":"1.0","event_id":"sha256:b95944266132ddf9fe63b156eddfb156b6117238c34469375a0569ee5248e75d"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:SYFY3NEEATD7RQ4TL6DNUKNCLD","target":"integrity","payload":{"note":"DOI is split by whitespace or line breaks in the printed bibliography. Reconstructed DOI 10.1111/biom.13706 resolves to 'Elastic Analysis of Irregularly or Sparsely Sampled Curves'. A reader following the printed text alone cannot reach it.","snippet":"Steyer, L., Stöcker, A., Greven, S.: Elastic analysis of irregularly or sparsely sam- pled curves. Biometrics79(3), 2103–2115 (2023). https://doi.org/10.1111/biom. 13706 Deep Shape Regression for Planar Curves with Multimodal Covariates 17","arxiv_id":"2607.19600","detector":"doi_compliance","evidence":{"ref_index":16,"verdict_class":"incontrovertible","resolved_title":"Elastic Analysis of Irregularly or Sparsely Sampled Curves","printed_excerpt":"10.1111/biom","reconstructed_doi":"10.1111/biom.13706"},"severity":"advisory","ref_index":16,"audited_at":"2026-08-01T12:29:37.276175Z","event_type":"pith.integrity.v1","detected_doi":"10.1111/biom.13706","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"d3036821d803ecd0c41e8fae4244b587921b557d95c63a7b116c930481e07649","paper_version":1,"verdict_class":"incontrovertible","resolved_title":"Elastic Analysis of Irregularly or Sparsely Sampled Curves","detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":15793,"payload_sha256":"4b98b17b72dd6dfe06af5cc71fcf507315d788190d387ef9e372099a0f76bfa2","signature_b64":"S5B3ujXyCpwychKgpaWYuNyN/clY+yCHdv7tPMvRQeEFqYqRnIK5FdszrPdgqUuAq+7nX1g2iWDwabm1ajSzAQ==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-01T12:33:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mE/7yVHuqmvUripvYQh2sergyq8UYd1aINhM47kacU6IRFnBpIzrmFQC7N82ZfZnjy8W+sibsRJN9hnKdKJ4CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T07:41:49.371007Z"},"content_sha256":"54f6d3a8059d9bf82c612f2da31601697d91af0deb1fb2c0b8e47b792820fdcc","schema_version":"1.0","event_id":"sha256:54f6d3a8059d9bf82c612f2da31601697d91af0deb1fb2c0b8e47b792820fdcc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SYFY3NEEATD7RQ4TL6DNUKNCLD/bundle.json","state_url":"https://pith.science/pith/SYFY3NEEATD7RQ4TL6DNUKNCLD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SYFY3NEEATD7RQ4TL6DNUKNCLD/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":"2026-08-04T07:41:49Z","links":{"resolver":"https://pith.science/pith/SYFY3NEEATD7RQ4TL6DNUKNCLD","bundle":"https://pith.science/pith/SYFY3NEEATD7RQ4TL6DNUKNCLD/bundle.json","state":"https://pith.science/pith/SYFY3NEEATD7RQ4TL6DNUKNCLD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SYFY3NEEATD7RQ4TL6DNUKNCLD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:SYFY3NEEATD7RQ4TL6DNUKNCLD","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"9693060eae6b76641e69ad1653a661ebc4b0ce61c05f0bffae4a282fd6928380","cross_cats_sorted":["cs.CV","cs.LG","q-bio.QM","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-21T22:04:17Z","title_canon_sha256":"1e1dfab892ca079cae864460cb0c8d0204d6a7dfa5efe8539a24b72acbe3ca2b"},"schema_version":"1.0","source":{"id":"2607.19600","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.19600","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"arxiv_version","alias_value":"2607.19600v1","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.19600","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"pith_short_12","alias_value":"SYFY3NEEATD7","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"pith_short_16","alias_value":"SYFY3NEEATD7RQ4T","created_at":"2026-07-23T00:23:58Z"},{"alias_kind":"pith_short_8","alias_value":"SYFY3NEE","created_at":"2026-07-23T00:23:58Z"}],"graph_snapshots":[{"event_id":"sha256:b95944266132ddf9fe63b156eddfb156b6117238c34469375a0569ee5248e75d","target":"graph","created_at":"2026-07-23T00:23:58Z","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/2607.19600/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The shape of a planar curve is the geometric information that remains once translation, rotation, scale and reparametrisation are removed and is of interest in many health applications, e.g. in neuroimaging. We propose a deep shape regression model for open planar curves that admits multimodal and high-dimensional covariates. Representing curves as complex-valued functions, we show that the conditional full Procrustes mean is the leading eigenfunction of the conditional covariance. To estimate this covariance surface, we propose a novel deep conditional covariance smoother with modality-specif","authors_text":"Hadya Yassin, Kerstin Ritter, Manuel Pfeuffer, Roshan Prakash Rane, Sonja Greven","cross_cats":["cs.CV","cs.LG","q-bio.QM","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-21T22:04:17Z","title":"Deep Shape Regression for Planar Curves with Multimodal Covariates"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.19600","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:b374261df766aed6b3b4026d47d1bbfa2cce84eaf1026f36b1d71b8f619ad511","target":"record","created_at":"2026-07-23T00:23:58Z","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":"9693060eae6b76641e69ad1653a661ebc4b0ce61c05f0bffae4a282fd6928380","cross_cats_sorted":["cs.CV","cs.LG","q-bio.QM","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-07-21T22:04:17Z","title_canon_sha256":"1e1dfab892ca079cae864460cb0c8d0204d6a7dfa5efe8539a24b72acbe3ca2b"},"schema_version":"1.0","source":{"id":"2607.19600","kind":"arxiv","version":1}},"canonical_sha256":"960b8db48404c7f8c3935f86da29a258d996d64cf8bab10bd4e4fc85d64401bb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"960b8db48404c7f8c3935f86da29a258d996d64cf8bab10bd4e4fc85d64401bb","first_computed_at":"2026-07-23T00:23:58.708132Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-23T00:23:58.708132Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AST5trT/KK01x40Z8+aMca6NEp8+94SyhQgiKQFd0gD30/EvwicN+Rc0XkcqQDXMPPGx7YBUCbAa1ZGmbujjCA==","signature_status":"signed_v1","signed_at":"2026-07-23T00:23:58.708993Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.19600","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b374261df766aed6b3b4026d47d1bbfa2cce84eaf1026f36b1d71b8f619ad511","sha256:b95944266132ddf9fe63b156eddfb156b6117238c34469375a0569ee5248e75d","sha256:54f6d3a8059d9bf82c612f2da31601697d91af0deb1fb2c0b8e47b792820fdcc"],"state_sha256":"41fa29bfa0961aec409202d8faa876a2f50d3f876de4b28b700acb534059d536"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VmFr4NeT1b4TnhzfcyId6xyFGv7Cp6fyVBOg/8w7gP5orG8+XljdP6//oQO+AJwhllNBuPBggkiNUKxROPTdAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T07:41:49.374173Z","bundle_sha256":"51239ae87294a602e10322d74e93e9c383e2690a12ab8ac0fd7faf9f6820a3cb"}}