{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:GGMNTUJ67F4HOV6OIZGXRED5HY","short_pith_number":"pith:GGMNTUJ6","canonical_record":{"source":{"id":"1707.06682","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-07-20T19:12:58Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"e92c0cced67006077ddd32217b68415dcffcb8aa89a93034aeab39a8ce0e7fb1","abstract_canon_sha256":"0375ea0ec0f23a022dbf59fd894153ccd79066753b439d0642ed7cd788887c2d"},"schema_version":"1.0"},"canonical_sha256":"3198d9d13ef9787757ce464d78907d3e0658370fa743b2631c613a4ecade243f","source":{"kind":"arxiv","id":"1707.06682","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.06682","created_at":"2026-05-18T00:39:51Z"},{"alias_kind":"arxiv_version","alias_value":"1707.06682v1","created_at":"2026-05-18T00:39:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.06682","created_at":"2026-05-18T00:39:51Z"},{"alias_kind":"pith_short_12","alias_value":"GGMNTUJ67F4H","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"GGMNTUJ67F4HOV6O","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"GGMNTUJ6","created_at":"2026-05-18T12:31:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:GGMNTUJ67F4HOV6OIZGXRED5HY","target":"record","payload":{"canonical_record":{"source":{"id":"1707.06682","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-07-20T19:12:58Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"e92c0cced67006077ddd32217b68415dcffcb8aa89a93034aeab39a8ce0e7fb1","abstract_canon_sha256":"0375ea0ec0f23a022dbf59fd894153ccd79066753b439d0642ed7cd788887c2d"},"schema_version":"1.0"},"canonical_sha256":"3198d9d13ef9787757ce464d78907d3e0658370fa743b2631c613a4ecade243f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:51.977803Z","signature_b64":"Z1y/jsX3/CY4p5KeZCLCOhbRe3BnsPLcoovQSOM4SfS3qdlqzJ3NPHf2Pv15BlrHRL9NPoD/YdBeO3/tQwAeAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3198d9d13ef9787757ce464d78907d3e0658370fa743b2631c613a4ecade243f","last_reissued_at":"2026-05-18T00:39:51.977140Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:51.977140Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1707.06682","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":"2026-05-18T00:39:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5u0/4/1bo+mHQ2Pm+LUXVzSV0yCfpnqdOPM6rK8EZwjYGXSkSAw/KghErG4m8Qeg35jMDn17woYMUJSPt/TiCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T13:38:28.461081Z"},"content_sha256":"d724450ea59e8ae6d716ab716579b0e1846239675d518d61e36c2ed3f1a8d608","schema_version":"1.0","event_id":"sha256:d724450ea59e8ae6d716ab716579b0e1846239675d518d61e36c2ed3f1a8d608"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:GGMNTUJ67F4HOV6OIZGXRED5HY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"stat.ML","authors_text":"Krisztian Buza, Regina Meszl\\'enyi, Zolt\\'an Vidny\\'anszky","submitted_at":"2017-07-20T19:12:58Z","abstract_excerpt":"Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our C"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.06682","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":"2026-05-18T00:39:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E9b0sCxGsCskRHql0m1G/I6FMsVu/td2SoAcDgGS/huTcWUW+fc6s//InLEgZ0OfVsQfTSIJ9P//l4J0+Rs3Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T13:38:28.461726Z"},"content_sha256":"0d092912f33219fd82cb48f25ba74a20a91a0858d3e35c8f12e160dcef2c1e07","schema_version":"1.0","event_id":"sha256:0d092912f33219fd82cb48f25ba74a20a91a0858d3e35c8f12e160dcef2c1e07"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GGMNTUJ67F4HOV6OIZGXRED5HY/bundle.json","state_url":"https://pith.science/pith/GGMNTUJ67F4HOV6OIZGXRED5HY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GGMNTUJ67F4HOV6OIZGXRED5HY/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":"2026-05-28T13:38:28Z","links":{"resolver":"https://pith.science/pith/GGMNTUJ67F4HOV6OIZGXRED5HY","bundle":"https://pith.science/pith/GGMNTUJ67F4HOV6OIZGXRED5HY/bundle.json","state":"https://pith.science/pith/GGMNTUJ67F4HOV6OIZGXRED5HY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GGMNTUJ67F4HOV6OIZGXRED5HY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:GGMNTUJ67F4HOV6OIZGXRED5HY","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":"0375ea0ec0f23a022dbf59fd894153ccd79066753b439d0642ed7cd788887c2d","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-07-20T19:12:58Z","title_canon_sha256":"e92c0cced67006077ddd32217b68415dcffcb8aa89a93034aeab39a8ce0e7fb1"},"schema_version":"1.0","source":{"id":"1707.06682","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1707.06682","created_at":"2026-05-18T00:39:51Z"},{"alias_kind":"arxiv_version","alias_value":"1707.06682v1","created_at":"2026-05-18T00:39:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1707.06682","created_at":"2026-05-18T00:39:51Z"},{"alias_kind":"pith_short_12","alias_value":"GGMNTUJ67F4H","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_16","alias_value":"GGMNTUJ67F4HOV6O","created_at":"2026-05-18T12:31:15Z"},{"alias_kind":"pith_short_8","alias_value":"GGMNTUJ6","created_at":"2026-05-18T12:31:15Z"}],"graph_snapshots":[{"event_id":"sha256:0d092912f33219fd82cb48f25ba74a20a91a0858d3e35c8f12e160dcef2c1e07","target":"graph","created_at":"2026-05-18T00:39:51Z","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":"Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our C","authors_text":"Krisztian Buza, Regina Meszl\\'enyi, Zolt\\'an Vidny\\'anszky","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-07-20T19:12:58Z","title":"Resting state fMRI functional connectivity-based classification using a convolutional neural network architecture"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1707.06682","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:d724450ea59e8ae6d716ab716579b0e1846239675d518d61e36c2ed3f1a8d608","target":"record","created_at":"2026-05-18T00:39:51Z","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":"0375ea0ec0f23a022dbf59fd894153ccd79066753b439d0642ed7cd788887c2d","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-07-20T19:12:58Z","title_canon_sha256":"e92c0cced67006077ddd32217b68415dcffcb8aa89a93034aeab39a8ce0e7fb1"},"schema_version":"1.0","source":{"id":"1707.06682","kind":"arxiv","version":1}},"canonical_sha256":"3198d9d13ef9787757ce464d78907d3e0658370fa743b2631c613a4ecade243f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3198d9d13ef9787757ce464d78907d3e0658370fa743b2631c613a4ecade243f","first_computed_at":"2026-05-18T00:39:51.977140Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:51.977140Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z1y/jsX3/CY4p5KeZCLCOhbRe3BnsPLcoovQSOM4SfS3qdlqzJ3NPHf2Pv15BlrHRL9NPoD/YdBeO3/tQwAeAA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:51.977803Z","signed_message":"canonical_sha256_bytes"},"source_id":"1707.06682","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d724450ea59e8ae6d716ab716579b0e1846239675d518d61e36c2ed3f1a8d608","sha256:0d092912f33219fd82cb48f25ba74a20a91a0858d3e35c8f12e160dcef2c1e07"],"state_sha256":"46021951c85f067a3a663bd527ce3e1e08f64824781f43335e5bfce9cbf54b07"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NKbSVX7sgodjFdHaocCwO/pKMAzhG7L0v1CzjayUUwk0k+A2hNrU+wH/cmzpSw6GJSoXClBb5ucZt+eRuMu2Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T13:38:28.466100Z","bundle_sha256":"48f4788ceaebee330cf57b0cfa10b6668f9518c5629def4858db754d92ae51d7"}}