{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:MO3JMMTFILCNVOTK2UY4S5X3PZ","short_pith_number":"pith:MO3JMMTF","canonical_record":{"source":{"id":"1806.03512","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.QM","submitted_at":"2018-06-09T17:32:50Z","cross_cats_sorted":[],"title_canon_sha256":"88783868d7823c12ef4163d15ff6497d3395e1e03a3d75b85bab90a416a601e4","abstract_canon_sha256":"e0a9e44f554a116739abe63293985d7222528e38b8f9587cf94113928b751ea6"},"schema_version":"1.0"},"canonical_sha256":"63b696326542c4daba6ad531c976fb7e568161ba5a21d1744af4781813402daa","source":{"kind":"arxiv","id":"1806.03512","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.03512","created_at":"2026-05-18T00:07:55Z"},{"alias_kind":"arxiv_version","alias_value":"1806.03512v1","created_at":"2026-05-18T00:07:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.03512","created_at":"2026-05-18T00:07:55Z"},{"alias_kind":"pith_short_12","alias_value":"MO3JMMTFILCN","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"MO3JMMTFILCNVOTK","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"MO3JMMTF","created_at":"2026-05-18T12:32:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:MO3JMMTFILCNVOTK2UY4S5X3PZ","target":"record","payload":{"canonical_record":{"source":{"id":"1806.03512","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.QM","submitted_at":"2018-06-09T17:32:50Z","cross_cats_sorted":[],"title_canon_sha256":"88783868d7823c12ef4163d15ff6497d3395e1e03a3d75b85bab90a416a601e4","abstract_canon_sha256":"e0a9e44f554a116739abe63293985d7222528e38b8f9587cf94113928b751ea6"},"schema_version":"1.0"},"canonical_sha256":"63b696326542c4daba6ad531c976fb7e568161ba5a21d1744af4781813402daa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:07:55.024699Z","signature_b64":"87KNA2/JezUUCz78rR6ef+r4xR3BxLUPSUtscpOn86BZfak2sjHV5i7uTq+dcOhX4WWYrwuh7wPJ1bB18rosBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"63b696326542c4daba6ad531c976fb7e568161ba5a21d1744af4781813402daa","last_reissued_at":"2026-05-18T00:07:55.023982Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:07:55.023982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.03512","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":"2026-05-18T00:07:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XsfjYTvg6hOgzv14DkgspPtoSr2PCssAcAmcE7BgBsnOisBcvC1DD/baKvGvfd3JjJG+aZHGMOkx7m5ECy7xAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T23:43:43.912435Z"},"content_sha256":"7a82527719e02e7fac7de6dab7b557bfb526ca11623055279abaad7aa1050ac9","schema_version":"1.0","event_id":"sha256:7a82527719e02e7fac7de6dab7b557bfb526ca11623055279abaad7aa1050ac9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:MO3JMMTFILCNVOTK2UY4S5X3PZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Structural neuroimaging as clinical predictor: a review of machine learning applications","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.QM","authors_text":"Alan C. Evans, Jos\\'e Mar\\'ia Mateos-P\\'erez, Mahsa Dadar, Mar\\'ia Lacalle-Aurioles, Yashar Zeighami, Yasser Iturria-Medina","submitted_at":"2018-06-09T17:32:50Z","abstract_excerpt":"In this paper, we provide an extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We specifically address practical problems commonly encountered in the literature, with the aim of helping researchers improve the application of these techniques in future works. Additionally, we survey how these algorithms are applied to a wide range of diseases and disorders (e.g. Alzheimer's disease (AD), Parkinson's disease (PD), autism, multiple sclerosis, traumatic brain injury, etc.) in order to provide a comprehensiv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.03512","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":"2026-05-18T00:07:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wBFxsrD3kUZNzx7/+u+mkZ0AqnDsm+nk+4GAYK+SRrXjNJ83QlMxYjWi0XjFqs85Q28eIuA2+G+4uSoVz3NgAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T23:43:43.913143Z"},"content_sha256":"5c9ccfd0ba05b497c61b951260626fc5861b7889cc36f25e07346e4b812e9f77","schema_version":"1.0","event_id":"sha256:5c9ccfd0ba05b497c61b951260626fc5861b7889cc36f25e07346e4b812e9f77"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MO3JMMTFILCNVOTK2UY4S5X3PZ/bundle.json","state_url":"https://pith.science/pith/MO3JMMTFILCNVOTK2UY4S5X3PZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MO3JMMTFILCNVOTK2UY4S5X3PZ/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":"2026-05-26T23:43:43Z","links":{"resolver":"https://pith.science/pith/MO3JMMTFILCNVOTK2UY4S5X3PZ","bundle":"https://pith.science/pith/MO3JMMTFILCNVOTK2UY4S5X3PZ/bundle.json","state":"https://pith.science/pith/MO3JMMTFILCNVOTK2UY4S5X3PZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MO3JMMTFILCNVOTK2UY4S5X3PZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:MO3JMMTFILCNVOTK2UY4S5X3PZ","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":"e0a9e44f554a116739abe63293985d7222528e38b8f9587cf94113928b751ea6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.QM","submitted_at":"2018-06-09T17:32:50Z","title_canon_sha256":"88783868d7823c12ef4163d15ff6497d3395e1e03a3d75b85bab90a416a601e4"},"schema_version":"1.0","source":{"id":"1806.03512","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.03512","created_at":"2026-05-18T00:07:55Z"},{"alias_kind":"arxiv_version","alias_value":"1806.03512v1","created_at":"2026-05-18T00:07:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.03512","created_at":"2026-05-18T00:07:55Z"},{"alias_kind":"pith_short_12","alias_value":"MO3JMMTFILCN","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_16","alias_value":"MO3JMMTFILCNVOTK","created_at":"2026-05-18T12:32:37Z"},{"alias_kind":"pith_short_8","alias_value":"MO3JMMTF","created_at":"2026-05-18T12:32:37Z"}],"graph_snapshots":[{"event_id":"sha256:5c9ccfd0ba05b497c61b951260626fc5861b7889cc36f25e07346e4b812e9f77","target":"graph","created_at":"2026-05-18T00:07:55Z","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 this paper, we provide an extensive overview of machine learning techniques applied to structural magnetic resonance imaging (MRI) data to obtain clinical classifiers. We specifically address practical problems commonly encountered in the literature, with the aim of helping researchers improve the application of these techniques in future works. Additionally, we survey how these algorithms are applied to a wide range of diseases and disorders (e.g. Alzheimer's disease (AD), Parkinson's disease (PD), autism, multiple sclerosis, traumatic brain injury, etc.) in order to provide a comprehensiv","authors_text":"Alan C. Evans, Jos\\'e Mar\\'ia Mateos-P\\'erez, Mahsa Dadar, Mar\\'ia Lacalle-Aurioles, Yashar Zeighami, Yasser Iturria-Medina","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.QM","submitted_at":"2018-06-09T17:32:50Z","title":"Structural neuroimaging as clinical predictor: a review of machine learning applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.03512","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":"sha256:7a82527719e02e7fac7de6dab7b557bfb526ca11623055279abaad7aa1050ac9","target":"record","created_at":"2026-05-18T00:07:55Z","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":"e0a9e44f554a116739abe63293985d7222528e38b8f9587cf94113928b751ea6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"q-bio.QM","submitted_at":"2018-06-09T17:32:50Z","title_canon_sha256":"88783868d7823c12ef4163d15ff6497d3395e1e03a3d75b85bab90a416a601e4"},"schema_version":"1.0","source":{"id":"1806.03512","kind":"arxiv","version":1}},"canonical_sha256":"63b696326542c4daba6ad531c976fb7e568161ba5a21d1744af4781813402daa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"63b696326542c4daba6ad531c976fb7e568161ba5a21d1744af4781813402daa","first_computed_at":"2026-05-18T00:07:55.023982Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:07:55.023982Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"87KNA2/JezUUCz78rR6ef+r4xR3BxLUPSUtscpOn86BZfak2sjHV5i7uTq+dcOhX4WWYrwuh7wPJ1bB18rosBA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:07:55.024699Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.03512","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7a82527719e02e7fac7de6dab7b557bfb526ca11623055279abaad7aa1050ac9","sha256:5c9ccfd0ba05b497c61b951260626fc5861b7889cc36f25e07346e4b812e9f77"],"state_sha256":"3780faff796e5961f87a83e955b30780646c1cbeb4aa0020a63ea1e9050d496a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"djvRyct8+X1otjpKOD14pcJpjJuWovkbshcg9Gc7e7qcDfqi9mUX/jMGQz4jWEOxGjh7HvbKWAoRQHs2sla0AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T23:43:43.916385Z","bundle_sha256":"70c5b60a67365ca3a7221cb0d6b022782137a524522a770c33a87c146b4d1b6a"}}