{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:QWRMTZUWDFX4PGTW652SYPZ4I3","short_pith_number":"pith:QWRMTZUW","schema_version":"1.0","canonical_sha256":"85a2c9e696196fc79a76f7752c3f3c46d3fc2453fd7f0d257719c85b7125ebfe","source":{"kind":"arxiv","id":"2209.07648","version":1},"attestation_state":"computed","paper":{"title":"Selecting a significance level in sequential testing procedures for community detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"stat.ME","authors_text":"Ian Barnett, Riddhi Pratim Ghosh","submitted_at":"2022-09-15T23:48:23Z","abstract_excerpt":"While there have been numerous sequential algorithms developed to estimate community structure in networks, there is little available guidance and study of what significance level or stopping parameter to use in these sequential testing procedures. Most algorithms rely on prespecifiying the number of communities or use an arbitrary stopping rule. We provide a principled approach to selecting a nominal significance level for sequential community detection procedures by controlling the tolerance ratio, defined as the ratio of underfitting and overfitting probability of estimating the number of c"},"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":"2209.07648","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2022-09-15T23:48:23Z","cross_cats_sorted":["stat.CO"],"title_canon_sha256":"f6681ecc487cbbe0643b1f517a0b00bff8e435095b059033e92a9cd394125a39","abstract_canon_sha256":"360cd178a5427096282a5b7666431726c6964fc09c7eaa416ed931ee96cc2a5e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:58:08.262373Z","signature_b64":"4eZDFxG5opNV5Afa8OpPvrSNnBtof7pKLy29OzkRf3TCqlEwNgxEf6pWcyqIojw8uoxav9ANv9ARKFzI0d2lDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"85a2c9e696196fc79a76f7752c3f3c46d3fc2453fd7f0d257719c85b7125ebfe","last_reissued_at":"2026-07-05T04:58:08.261955Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:58:08.261955Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Selecting a significance level in sequential testing procedures for community detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.CO"],"primary_cat":"stat.ME","authors_text":"Ian Barnett, Riddhi Pratim Ghosh","submitted_at":"2022-09-15T23:48:23Z","abstract_excerpt":"While there have been numerous sequential algorithms developed to estimate community structure in networks, there is little available guidance and study of what significance level or stopping parameter to use in these sequential testing procedures. Most algorithms rely on prespecifiying the number of communities or use an arbitrary stopping rule. We provide a principled approach to selecting a nominal significance level for sequential community detection procedures by controlling the tolerance ratio, defined as the ratio of underfitting and overfitting probability of estimating the number of c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2209.07648","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2209.07648/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2209.07648","created_at":"2026-07-05T04:58:08.262012+00:00"},{"alias_kind":"arxiv_version","alias_value":"2209.07648v1","created_at":"2026-07-05T04:58:08.262012+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2209.07648","created_at":"2026-07-05T04:58:08.262012+00:00"},{"alias_kind":"pith_short_12","alias_value":"QWRMTZUWDFX4","created_at":"2026-07-05T04:58:08.262012+00:00"},{"alias_kind":"pith_short_16","alias_value":"QWRMTZUWDFX4PGTW","created_at":"2026-07-05T04:58:08.262012+00:00"},{"alias_kind":"pith_short_8","alias_value":"QWRMTZUW","created_at":"2026-07-05T04:58:08.262012+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/QWRMTZUWDFX4PGTW652SYPZ4I3","json":"https://pith.science/pith/QWRMTZUWDFX4PGTW652SYPZ4I3.json","graph_json":"https://pith.science/api/pith-number/QWRMTZUWDFX4PGTW652SYPZ4I3/graph.json","events_json":"https://pith.science/api/pith-number/QWRMTZUWDFX4PGTW652SYPZ4I3/events.json","paper":"https://pith.science/paper/QWRMTZUW"},"agent_actions":{"view_html":"https://pith.science/pith/QWRMTZUWDFX4PGTW652SYPZ4I3","download_json":"https://pith.science/pith/QWRMTZUWDFX4PGTW652SYPZ4I3.json","view_paper":"https://pith.science/paper/QWRMTZUW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2209.07648&json=true","fetch_graph":"https://pith.science/api/pith-number/QWRMTZUWDFX4PGTW652SYPZ4I3/graph.json","fetch_events":"https://pith.science/api/pith-number/QWRMTZUWDFX4PGTW652SYPZ4I3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QWRMTZUWDFX4PGTW652SYPZ4I3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QWRMTZUWDFX4PGTW652SYPZ4I3/action/storage_attestation","attest_author":"https://pith.science/pith/QWRMTZUWDFX4PGTW652SYPZ4I3/action/author_attestation","sign_citation":"https://pith.science/pith/QWRMTZUWDFX4PGTW652SYPZ4I3/action/citation_signature","submit_replication":"https://pith.science/pith/QWRMTZUWDFX4PGTW652SYPZ4I3/action/replication_record"}},"created_at":"2026-07-05T04:58:08.262012+00:00","updated_at":"2026-07-05T04:58:08.262012+00:00"}