{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:OSSDYCQTAM2EWTJ2242O2G5VMP","short_pith_number":"pith:OSSDYCQT","canonical_record":{"source":{"id":"1801.05017","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-01-15T21:17:37Z","cross_cats_sorted":[],"title_canon_sha256":"b0fa298b571d3aaadb73219b1b2ff1409cc9497e6edeeb377de8b72a93f8d65f","abstract_canon_sha256":"f5e6e184e987ad2b00050dcb4278f335b014059358ac005b4c1cd97aefe3956e"},"schema_version":"1.0"},"canonical_sha256":"74a43c0a1303344b4d3ad734ed1bb563e9fcfedf6b9e54e3d7a3589ef31f202f","source":{"kind":"arxiv","id":"1801.05017","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.05017","created_at":"2026-05-18T00:25:50Z"},{"alias_kind":"arxiv_version","alias_value":"1801.05017v1","created_at":"2026-05-18T00:25:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.05017","created_at":"2026-05-18T00:25:50Z"},{"alias_kind":"pith_short_12","alias_value":"OSSDYCQTAM2E","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OSSDYCQTAM2EWTJ2","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OSSDYCQT","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:OSSDYCQTAM2EWTJ2242O2G5VMP","target":"record","payload":{"canonical_record":{"source":{"id":"1801.05017","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-01-15T21:17:37Z","cross_cats_sorted":[],"title_canon_sha256":"b0fa298b571d3aaadb73219b1b2ff1409cc9497e6edeeb377de8b72a93f8d65f","abstract_canon_sha256":"f5e6e184e987ad2b00050dcb4278f335b014059358ac005b4c1cd97aefe3956e"},"schema_version":"1.0"},"canonical_sha256":"74a43c0a1303344b4d3ad734ed1bb563e9fcfedf6b9e54e3d7a3589ef31f202f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:25:50.291984Z","signature_b64":"64rOfVyaj2x9VHlKPenWT8ENrVT1Cu/jqaQer/ODbIcH9iatY33+3tC5dIIot/2s7MKLQoDuCouuhBqWSAgVAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"74a43c0a1303344b4d3ad734ed1bb563e9fcfedf6b9e54e3d7a3589ef31f202f","last_reissued_at":"2026-05-18T00:25:50.291261Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:25:50.291261Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1801.05017","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":"2026-05-18T00:25:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fEKCEzztbeYvORpSlWlTWHYswpGTzhSnPrh6Sf/1O9w+tbsxjnd4CuIaC/DoeX9Mm+Z39/PsMCyobjIGj59xDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T22:01:29.196701Z"},"content_sha256":"12e5906fdc7ce8e6841d3cc8d00ed3b5f98598a5bc021bc6b08af84785002aa1","schema_version":"1.0","event_id":"sha256:12e5906fdc7ce8e6841d3cc8d00ed3b5f98598a5bc021bc6b08af84785002aa1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:OSSDYCQTAM2EWTJ2242O2G5VMP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hypergraph based Subnetwork Extraction using Fusion of Task and Rest Functional Connectivity","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Chendi Wang, Rafeef Abugharbieh","submitted_at":"2018-01-15T21:17:37Z","abstract_excerpt":"Functional subnetwork extraction is commonly used to explore the brain's modular structure. However, reliable subnetwork extraction from functional magnetic resonance imaging (fMRI) data remains challenging due to the pronounced noise in neuroimaging data. In this paper, we proposed a high order relation informed approach based on hypergraph to combine the information from multi-task data and resting state data to improve subnetwork extraction. Our assumption is that task data can be beneficial for the subnetwork extraction process, since the repeatedly activated nodes involved in diverse task"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.05017","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":"2026-05-18T00:25:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mZYghn4T/VXFFJ2+E4XsYSc7sDjwR4P12c2rdBHKZJnanuPsw1X35akK5YovV1Dqvnmn1uPdAoHS5EUEEK3pBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T22:01:29.197239Z"},"content_sha256":"eca95f36d6bba90b118dd89c4e0e34c7cf4d9df8c3df9ab960e6d562670bc557","schema_version":"1.0","event_id":"sha256:eca95f36d6bba90b118dd89c4e0e34c7cf4d9df8c3df9ab960e6d562670bc557"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OSSDYCQTAM2EWTJ2242O2G5VMP/bundle.json","state_url":"https://pith.science/pith/OSSDYCQTAM2EWTJ2242O2G5VMP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OSSDYCQTAM2EWTJ2242O2G5VMP/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":"2026-05-27T22:01:29Z","links":{"resolver":"https://pith.science/pith/OSSDYCQTAM2EWTJ2242O2G5VMP","bundle":"https://pith.science/pith/OSSDYCQTAM2EWTJ2242O2G5VMP/bundle.json","state":"https://pith.science/pith/OSSDYCQTAM2EWTJ2242O2G5VMP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OSSDYCQTAM2EWTJ2242O2G5VMP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:OSSDYCQTAM2EWTJ2242O2G5VMP","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":"f5e6e184e987ad2b00050dcb4278f335b014059358ac005b4c1cd97aefe3956e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-01-15T21:17:37Z","title_canon_sha256":"b0fa298b571d3aaadb73219b1b2ff1409cc9497e6edeeb377de8b72a93f8d65f"},"schema_version":"1.0","source":{"id":"1801.05017","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1801.05017","created_at":"2026-05-18T00:25:50Z"},{"alias_kind":"arxiv_version","alias_value":"1801.05017v1","created_at":"2026-05-18T00:25:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1801.05017","created_at":"2026-05-18T00:25:50Z"},{"alias_kind":"pith_short_12","alias_value":"OSSDYCQTAM2E","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OSSDYCQTAM2EWTJ2","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OSSDYCQT","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:eca95f36d6bba90b118dd89c4e0e34c7cf4d9df8c3df9ab960e6d562670bc557","target":"graph","created_at":"2026-05-18T00:25:50Z","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":"Functional subnetwork extraction is commonly used to explore the brain's modular structure. However, reliable subnetwork extraction from functional magnetic resonance imaging (fMRI) data remains challenging due to the pronounced noise in neuroimaging data. In this paper, we proposed a high order relation informed approach based on hypergraph to combine the information from multi-task data and resting state data to improve subnetwork extraction. Our assumption is that task data can be beneficial for the subnetwork extraction process, since the repeatedly activated nodes involved in diverse task","authors_text":"Chendi Wang, Rafeef Abugharbieh","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-01-15T21:17:37Z","title":"Hypergraph based Subnetwork Extraction using Fusion of Task and Rest Functional Connectivity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1801.05017","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":"sha256:12e5906fdc7ce8e6841d3cc8d00ed3b5f98598a5bc021bc6b08af84785002aa1","target":"record","created_at":"2026-05-18T00:25:50Z","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":"f5e6e184e987ad2b00050dcb4278f335b014059358ac005b4c1cd97aefe3956e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2018-01-15T21:17:37Z","title_canon_sha256":"b0fa298b571d3aaadb73219b1b2ff1409cc9497e6edeeb377de8b72a93f8d65f"},"schema_version":"1.0","source":{"id":"1801.05017","kind":"arxiv","version":1}},"canonical_sha256":"74a43c0a1303344b4d3ad734ed1bb563e9fcfedf6b9e54e3d7a3589ef31f202f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"74a43c0a1303344b4d3ad734ed1bb563e9fcfedf6b9e54e3d7a3589ef31f202f","first_computed_at":"2026-05-18T00:25:50.291261Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:25:50.291261Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"64rOfVyaj2x9VHlKPenWT8ENrVT1Cu/jqaQer/ODbIcH9iatY33+3tC5dIIot/2s7MKLQoDuCouuhBqWSAgVAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:25:50.291984Z","signed_message":"canonical_sha256_bytes"},"source_id":"1801.05017","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:12e5906fdc7ce8e6841d3cc8d00ed3b5f98598a5bc021bc6b08af84785002aa1","sha256:eca95f36d6bba90b118dd89c4e0e34c7cf4d9df8c3df9ab960e6d562670bc557"],"state_sha256":"1fb018e8cd233e80cd6d2c79e8e94975fe5d0e7a73a79bd1c08a0bd1157c18f5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Re26SkGzojVGcfeUvqLbv/lhD+sg2dfguPWuirhsQqiF3poHWD33rM1fO1Urv1xalbIjuuLu0f1TLMvNXvnvCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T22:01:29.200500Z","bundle_sha256":"e514415f7619021fd10b751bf8d6eb51670f78568720a282510dd54bebab753e"}}