{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:V4OV77BO5XVCQ2XLGYHFX3MV4W","short_pith_number":"pith:V4OV77BO","schema_version":"1.0","canonical_sha256":"af1d5ffc2eedea286aeb360e5bed95e582efb1f27447bef3474fdb6a547bb716","source":{"kind":"arxiv","id":"1409.3059","version":4},"attestation_state":"computed","paper":{"title":"Model selection and hypothesis testing for large-scale network models with overlapping groups","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":["cond-mat.dis-nn","cs.SI","physics.comp-ph","physics.soc-ph"],"primary_cat":"physics.data-an","authors_text":"Tiago P. Peixoto","submitted_at":"2014-09-10T13:17:51Z","abstract_excerpt":"The effort to understand network systems in increasing detail has resulted in a diversity of methods designed to extract their large-scale structure from data. Unfortunately, many of these methods yield diverging descriptions of the same network, making both the comparison and understanding of their results a difficult challenge. A possible solution to this outstanding issue is to shift the focus away from ad hoc methods and move towards more principled approaches based on statistical inference of generative models. As a result, we face instead the more well-defined task of selecting between 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":"1409.3059","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","primary_cat":"physics.data-an","submitted_at":"2014-09-10T13:17:51Z","cross_cats_sorted":["cond-mat.dis-nn","cs.SI","physics.comp-ph","physics.soc-ph"],"title_canon_sha256":"b9b66c35cb2e60152185a03fbc28504a7a46ffe2f83586edde2e65f996bcffab","abstract_canon_sha256":"68ebf6be241aaf7946e9c21e2ff05f77d28b28fd2b2fd190da6411983023c805"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:20:19.791063Z","signature_b64":"XVIAcw0VelAhCm4PC4U057ucEYUutD17xofUgD0nU1u+2RvpDJD8+ihgnAbH8e/5B84euLqD2Cq3rM3ZRFfaBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"af1d5ffc2eedea286aeb360e5bed95e582efb1f27447bef3474fdb6a547bb716","last_reissued_at":"2026-05-18T02:20:19.790443Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:20:19.790443Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Model selection and hypothesis testing for large-scale network models with overlapping groups","license":"http://creativecommons.org/licenses/by-nc-sa/3.0/","headline":"","cross_cats":["cond-mat.dis-nn","cs.SI","physics.comp-ph","physics.soc-ph"],"primary_cat":"physics.data-an","authors_text":"Tiago P. Peixoto","submitted_at":"2014-09-10T13:17:51Z","abstract_excerpt":"The effort to understand network systems in increasing detail has resulted in a diversity of methods designed to extract their large-scale structure from data. Unfortunately, many of these methods yield diverging descriptions of the same network, making both the comparison and understanding of their results a difficult challenge. A possible solution to this outstanding issue is to shift the focus away from ad hoc methods and move towards more principled approaches based on statistical inference of generative models. As a result, we face instead the more well-defined task of selecting between c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1409.3059","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":"1409.3059","created_at":"2026-05-18T02:20:19.790531+00:00"},{"alias_kind":"arxiv_version","alias_value":"1409.3059v4","created_at":"2026-05-18T02:20:19.790531+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1409.3059","created_at":"2026-05-18T02:20:19.790531+00:00"},{"alias_kind":"pith_short_12","alias_value":"V4OV77BO5XVC","created_at":"2026-05-18T12:28:52.271510+00:00"},{"alias_kind":"pith_short_16","alias_value":"V4OV77BO5XVCQ2XL","created_at":"2026-05-18T12:28:52.271510+00:00"},{"alias_kind":"pith_short_8","alias_value":"V4OV77BO","created_at":"2026-05-18T12:28:52.271510+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/V4OV77BO5XVCQ2XLGYHFX3MV4W","json":"https://pith.science/pith/V4OV77BO5XVCQ2XLGYHFX3MV4W.json","graph_json":"https://pith.science/api/pith-number/V4OV77BO5XVCQ2XLGYHFX3MV4W/graph.json","events_json":"https://pith.science/api/pith-number/V4OV77BO5XVCQ2XLGYHFX3MV4W/events.json","paper":"https://pith.science/paper/V4OV77BO"},"agent_actions":{"view_html":"https://pith.science/pith/V4OV77BO5XVCQ2XLGYHFX3MV4W","download_json":"https://pith.science/pith/V4OV77BO5XVCQ2XLGYHFX3MV4W.json","view_paper":"https://pith.science/paper/V4OV77BO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1409.3059&json=true","fetch_graph":"https://pith.science/api/pith-number/V4OV77BO5XVCQ2XLGYHFX3MV4W/graph.json","fetch_events":"https://pith.science/api/pith-number/V4OV77BO5XVCQ2XLGYHFX3MV4W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/V4OV77BO5XVCQ2XLGYHFX3MV4W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/V4OV77BO5XVCQ2XLGYHFX3MV4W/action/storage_attestation","attest_author":"https://pith.science/pith/V4OV77BO5XVCQ2XLGYHFX3MV4W/action/author_attestation","sign_citation":"https://pith.science/pith/V4OV77BO5XVCQ2XLGYHFX3MV4W/action/citation_signature","submit_replication":"https://pith.science/pith/V4OV77BO5XVCQ2XLGYHFX3MV4W/action/replication_record"}},"created_at":"2026-05-18T02:20:19.790531+00:00","updated_at":"2026-05-18T02:20:19.790531+00:00"}