{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:Q5SWAVP6FQTVP25GSASP2CJSRY","short_pith_number":"pith:Q5SWAVP6","schema_version":"1.0","canonical_sha256":"87656055fe2c2757eba69024fd09328e07829b9162769993320465323d129f85","source":{"kind":"arxiv","id":"1611.06893","version":4},"attestation_state":"computed","paper":{"title":"A statistical model for brain networks inferred from large-scale electrophysiological signals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Catalina Obando, Fabrizio De Vico Fallani","submitted_at":"2016-11-21T16:38:06Z","abstract_excerpt":"Network science has been extensively developed to characterize structural properties of complex systems, including brain networks inferred from neuroimaging data. As a result of the inference process, networks estimated from experimentally obtained biological data, represent one instance of a larger number of realizations with similar intrinsic topology. A modeling approach is therefore needed to support statistical inference on the bottom-up local connectivity mechanisms influencing the formation of the estimated brain networks. We adopted a statistical model based on exponential random graph"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1611.06893","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2016-11-21T16:38:06Z","cross_cats_sorted":[],"title_canon_sha256":"4926e7c204795449c04bcd746e3211106a37ef6f7885770a63c173da89a6cdaf","abstract_canon_sha256":"7c0b1832a6f301e238fb3b44671c7a690ec88c3a1282f480449540f09765857d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:49:02.245049Z","signature_b64":"wMSw30nFn0wMz8kxFIxa5QdcTX7vg8uCm5GK6ixaPZFCYsqtexGRR0xs5ijpHo0Xc/ad99ftwWQVq1+N/HWmCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"87656055fe2c2757eba69024fd09328e07829b9162769993320465323d129f85","last_reissued_at":"2026-05-18T00:49:02.244285Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:49:02.244285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A statistical model for brain networks inferred from large-scale electrophysiological signals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Catalina Obando, Fabrizio De Vico Fallani","submitted_at":"2016-11-21T16:38:06Z","abstract_excerpt":"Network science has been extensively developed to characterize structural properties of complex systems, including brain networks inferred from neuroimaging data. As a result of the inference process, networks estimated from experimentally obtained biological data, represent one instance of a larger number of realizations with similar intrinsic topology. A modeling approach is therefore needed to support statistical inference on the bottom-up local connectivity mechanisms influencing the formation of the estimated brain networks. We adopted a statistical model based on exponential random graph"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.06893","kind":"arxiv","version":4},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1611.06893","created_at":"2026-05-18T00:49:02.244427+00:00"},{"alias_kind":"arxiv_version","alias_value":"1611.06893v4","created_at":"2026-05-18T00:49:02.244427+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.06893","created_at":"2026-05-18T00:49:02.244427+00:00"},{"alias_kind":"pith_short_12","alias_value":"Q5SWAVP6FQTV","created_at":"2026-05-18T12:30:39.010887+00:00"},{"alias_kind":"pith_short_16","alias_value":"Q5SWAVP6FQTVP25G","created_at":"2026-05-18T12:30:39.010887+00:00"},{"alias_kind":"pith_short_8","alias_value":"Q5SWAVP6","created_at":"2026-05-18T12:30:39.010887+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY","json":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY.json","graph_json":"https://pith.science/api/pith-number/Q5SWAVP6FQTVP25GSASP2CJSRY/graph.json","events_json":"https://pith.science/api/pith-number/Q5SWAVP6FQTVP25GSASP2CJSRY/events.json","paper":"https://pith.science/paper/Q5SWAVP6"},"agent_actions":{"view_html":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY","download_json":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY.json","view_paper":"https://pith.science/paper/Q5SWAVP6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1611.06893&json=true","fetch_graph":"https://pith.science/api/pith-number/Q5SWAVP6FQTVP25GSASP2CJSRY/graph.json","fetch_events":"https://pith.science/api/pith-number/Q5SWAVP6FQTVP25GSASP2CJSRY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY/action/storage_attestation","attest_author":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY/action/author_attestation","sign_citation":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY/action/citation_signature","submit_replication":"https://pith.science/pith/Q5SWAVP6FQTVP25GSASP2CJSRY/action/replication_record"}},"created_at":"2026-05-18T00:49:02.244427+00:00","updated_at":"2026-05-18T00:49:02.244427+00:00"}