{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:AUZC6J4WDCPU6EEOWDYYP7AATP","short_pith_number":"pith:AUZC6J4W","schema_version":"1.0","canonical_sha256":"05322f2796189f4f108eb0f187fc009bfa5b1199c6f3fee1313253d5b3efb1d5","source":{"kind":"arxiv","id":"1610.06511","version":3},"attestation_state":"computed","paper":{"title":"Community extraction in multilayer networks with heterogeneous community structure","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.soc-ph","stat.ME"],"primary_cat":"cs.SI","authors_text":"Andrew B. Nobel, James D. Wilson, John Palowitch, Shankar Bhamidi","submitted_at":"2016-10-20T17:35:42Z","abstract_excerpt":"Multilayer networks are a useful way to capture and model multiple, binary or weighted relationships among a fixed group of objects. While community detection has proven to be a useful exploratory technique for the analysis of single-layer networks, the development of community detection methods for multilayer networks is still in its infancy. We propose and investigate a procedure, called Multilayer Extraction, that identifies densely connected vertex-layer sets in multilayer networks. Multilayer Extraction makes use of a significance based score that quantifies the connectivity of an observe"},"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":"1610.06511","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SI","submitted_at":"2016-10-20T17:35:42Z","cross_cats_sorted":["physics.soc-ph","stat.ME"],"title_canon_sha256":"2664de50ee2dc51dc6f66eac91152ec852a85e434a54776853e7d30ce09a25d0","abstract_canon_sha256":"52a5e96264ba21304ad0df6c7313039b31569dccd7f026f4a7cef769d4779e02"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:31:03.174470Z","signature_b64":"jmJiFuwVPo9ZQkREe1pzbo9xAO7CNZXMSjYlwPllv8mrGJsyDzkB5+Gfqc617y0pZKqcjJjRRX3bC4ZbIWaLDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"05322f2796189f4f108eb0f187fc009bfa5b1199c6f3fee1313253d5b3efb1d5","last_reissued_at":"2026-05-18T00:31:03.173372Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:31:03.173372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Community extraction in multilayer networks with heterogeneous community structure","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.soc-ph","stat.ME"],"primary_cat":"cs.SI","authors_text":"Andrew B. Nobel, James D. Wilson, John Palowitch, Shankar Bhamidi","submitted_at":"2016-10-20T17:35:42Z","abstract_excerpt":"Multilayer networks are a useful way to capture and model multiple, binary or weighted relationships among a fixed group of objects. While community detection has proven to be a useful exploratory technique for the analysis of single-layer networks, the development of community detection methods for multilayer networks is still in its infancy. We propose and investigate a procedure, called Multilayer Extraction, that identifies densely connected vertex-layer sets in multilayer networks. Multilayer Extraction makes use of a significance based score that quantifies the connectivity of an observe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1610.06511","kind":"arxiv","version":3},"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":"1610.06511","created_at":"2026-05-18T00:31:03.173783+00:00"},{"alias_kind":"arxiv_version","alias_value":"1610.06511v3","created_at":"2026-05-18T00:31:03.173783+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1610.06511","created_at":"2026-05-18T00:31:03.173783+00:00"},{"alias_kind":"pith_short_12","alias_value":"AUZC6J4WDCPU","created_at":"2026-05-18T12:30:07.202191+00:00"},{"alias_kind":"pith_short_16","alias_value":"AUZC6J4WDCPU6EEO","created_at":"2026-05-18T12:30:07.202191+00:00"},{"alias_kind":"pith_short_8","alias_value":"AUZC6J4W","created_at":"2026-05-18T12:30:07.202191+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/AUZC6J4WDCPU6EEOWDYYP7AATP","json":"https://pith.science/pith/AUZC6J4WDCPU6EEOWDYYP7AATP.json","graph_json":"https://pith.science/api/pith-number/AUZC6J4WDCPU6EEOWDYYP7AATP/graph.json","events_json":"https://pith.science/api/pith-number/AUZC6J4WDCPU6EEOWDYYP7AATP/events.json","paper":"https://pith.science/paper/AUZC6J4W"},"agent_actions":{"view_html":"https://pith.science/pith/AUZC6J4WDCPU6EEOWDYYP7AATP","download_json":"https://pith.science/pith/AUZC6J4WDCPU6EEOWDYYP7AATP.json","view_paper":"https://pith.science/paper/AUZC6J4W","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1610.06511&json=true","fetch_graph":"https://pith.science/api/pith-number/AUZC6J4WDCPU6EEOWDYYP7AATP/graph.json","fetch_events":"https://pith.science/api/pith-number/AUZC6J4WDCPU6EEOWDYYP7AATP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AUZC6J4WDCPU6EEOWDYYP7AATP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AUZC6J4WDCPU6EEOWDYYP7AATP/action/storage_attestation","attest_author":"https://pith.science/pith/AUZC6J4WDCPU6EEOWDYYP7AATP/action/author_attestation","sign_citation":"https://pith.science/pith/AUZC6J4WDCPU6EEOWDYYP7AATP/action/citation_signature","submit_replication":"https://pith.science/pith/AUZC6J4WDCPU6EEOWDYYP7AATP/action/replication_record"}},"created_at":"2026-05-18T00:31:03.173783+00:00","updated_at":"2026-05-18T00:31:03.173783+00:00"}