{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:GKGI7MIBSCVJVATPVLRTUSQBEA","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":"7ebaff88421b9ba9201d143f10dcad7ffe67d4cb2f8e3d20025be83da4f0c4ea","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-11T19:30:20Z","title_canon_sha256":"519806c06c6f076e31de255c1c14cc0ec72c81dfd9c983f17918b3bcc6294df0"},"schema_version":"1.0","source":{"id":"1806.04209","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04209","created_at":"2026-05-18T00:13:21Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04209v2","created_at":"2026-05-18T00:13:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04209","created_at":"2026-05-18T00:13:21Z"},{"alias_kind":"pith_short_12","alias_value":"GKGI7MIBSCVJ","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_16","alias_value":"GKGI7MIBSCVJVATP","created_at":"2026-05-18T12:32:25Z"},{"alias_kind":"pith_short_8","alias_value":"GKGI7MIB","created_at":"2026-05-18T12:32:25Z"}],"graph_snapshots":[{"event_id":"sha256:7b75b8d633c09fb79d49cf63f6d7de5dfbe16d21f7f1035ac0ba104a60d6416a","target":"graph","created_at":"2026-05-18T00:13:21Z","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":"Resting-state functional MRI (rs-fMRI) scans hold the potential to serve as a diagnostic or prognostic tool for a wide variety of conditions, such as autism, Alzheimer's disease, and stroke. While a growing number of studies have demonstrated the promise of machine learning algorithms for rs-fMRI based clinical or behavioral prediction, most prior models have been limited in their capacity to exploit the richness of the data. For example, classification techniques applied to rs-fMRI often rely on region-based summary statistics and/or linear models. In this work, we propose a novel volumetric ","authors_text":"Amy Kuceyeski, Keith Jamison, Meenakshi Khosla, Mert Sabuncu","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-11T19:30:20Z","title":"3D Convolutional Neural Networks for Classification of Functional Connectomes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04209","kind":"arxiv","version":2},"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":"sha256:11d5a9a9abe4c52601a93b9a3b76f1878e664631d38aa69ec47e06391e12bbf2","target":"record","created_at":"2026-05-18T00:13:21Z","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":"7ebaff88421b9ba9201d143f10dcad7ffe67d4cb2f8e3d20025be83da4f0c4ea","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-06-11T19:30:20Z","title_canon_sha256":"519806c06c6f076e31de255c1c14cc0ec72c81dfd9c983f17918b3bcc6294df0"},"schema_version":"1.0","source":{"id":"1806.04209","kind":"arxiv","version":2}},"canonical_sha256":"328c8fb10190aa9a826faae33a4a012027f8c0445c48395f80c5268005635245","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"328c8fb10190aa9a826faae33a4a012027f8c0445c48395f80c5268005635245","first_computed_at":"2026-05-18T00:13:21.185898Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:21.185898Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ztn9o2fUnt4gtpkBWXoC+RwBIx+0bpZq+7xEtcwXARO8pzje8Ni3/EyqsHHSVKJTXtMT1y2zev9KqsVgTyLXBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:21.186480Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.04209","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:11d5a9a9abe4c52601a93b9a3b76f1878e664631d38aa69ec47e06391e12bbf2","sha256:7b75b8d633c09fb79d49cf63f6d7de5dfbe16d21f7f1035ac0ba104a60d6416a"],"state_sha256":"1a10a055b0115d4ff3db72f5c577a1f83a9c3904abdf791bed71c031fd4ce7a5"}