{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:YCH34NDTJQLZ5VCZ7563F56WQ2","short_pith_number":"pith:YCH34NDT","schema_version":"1.0","canonical_sha256":"c08fbe34734c179ed459ff7db2f7d686b895f32f321b1eb32772702133e242b5","source":{"kind":"arxiv","id":"1704.01459","version":1},"attestation_state":"computed","paper":{"title":"Statistical properties of interaction parameter estimates in direct coupling analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.dis-nn","cond-mat.stat-mech"],"primary_cat":"physics.data-an","authors_text":"Erik Aurell, Jukka Corander, Yingying Xu, Yoshiyuki Kabashima","submitted_at":"2017-04-05T14:53:55Z","abstract_excerpt":"We consider the statistical properties of interaction parameter estimates obtained by the direct coupling analysis (DCA) approach to learning interactions from large data sets. Assuming that the data are generated from a random background distribution, we determine the distribution of inferred interactions. Two inference methods are considered: the L2 regularized naive mean-field inference procedure (regularized least squares, RLS), and the pseudo-likelihood maximization (plmDCA). For RLS we also study a model where the data matrix elements are real numbers, identically and independently gener"},"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":"1704.01459","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.data-an","submitted_at":"2017-04-05T14:53:55Z","cross_cats_sorted":["cond-mat.dis-nn","cond-mat.stat-mech"],"title_canon_sha256":"a041e06354710a35780fcab5a7372d00cd7b62dca4d11ae0d8de27d4a6793019","abstract_canon_sha256":"bfa216ac44a2377d138f41a00384b7a95223a48cac3ffda8cf9e715e97476f53"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:46:54.856676Z","signature_b64":"rmwDvT3g4Zooi2yzZD6I/IC9x0EBt/fsXeRO+/gjfltLImpyMbF9eQxZaBrUZF7KT3jK5Yd1is1kuZQApZFrCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c08fbe34734c179ed459ff7db2f7d686b895f32f321b1eb32772702133e242b5","last_reissued_at":"2026-05-18T00:46:54.856117Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:46:54.856117Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Statistical properties of interaction parameter estimates in direct coupling analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.dis-nn","cond-mat.stat-mech"],"primary_cat":"physics.data-an","authors_text":"Erik Aurell, Jukka Corander, Yingying Xu, Yoshiyuki Kabashima","submitted_at":"2017-04-05T14:53:55Z","abstract_excerpt":"We consider the statistical properties of interaction parameter estimates obtained by the direct coupling analysis (DCA) approach to learning interactions from large data sets. Assuming that the data are generated from a random background distribution, we determine the distribution of inferred interactions. Two inference methods are considered: the L2 regularized naive mean-field inference procedure (regularized least squares, RLS), and the pseudo-likelihood maximization (plmDCA). For RLS we also study a model where the data matrix elements are real numbers, identically and independently gener"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.01459","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1704.01459","created_at":"2026-05-18T00:46:54.856207+00:00"},{"alias_kind":"arxiv_version","alias_value":"1704.01459v1","created_at":"2026-05-18T00:46:54.856207+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.01459","created_at":"2026-05-18T00:46:54.856207+00:00"},{"alias_kind":"pith_short_12","alias_value":"YCH34NDTJQLZ","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_16","alias_value":"YCH34NDTJQLZ5VCZ","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_8","alias_value":"YCH34NDT","created_at":"2026-05-18T12:31:56.362134+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/YCH34NDTJQLZ5VCZ7563F56WQ2","json":"https://pith.science/pith/YCH34NDTJQLZ5VCZ7563F56WQ2.json","graph_json":"https://pith.science/api/pith-number/YCH34NDTJQLZ5VCZ7563F56WQ2/graph.json","events_json":"https://pith.science/api/pith-number/YCH34NDTJQLZ5VCZ7563F56WQ2/events.json","paper":"https://pith.science/paper/YCH34NDT"},"agent_actions":{"view_html":"https://pith.science/pith/YCH34NDTJQLZ5VCZ7563F56WQ2","download_json":"https://pith.science/pith/YCH34NDTJQLZ5VCZ7563F56WQ2.json","view_paper":"https://pith.science/paper/YCH34NDT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1704.01459&json=true","fetch_graph":"https://pith.science/api/pith-number/YCH34NDTJQLZ5VCZ7563F56WQ2/graph.json","fetch_events":"https://pith.science/api/pith-number/YCH34NDTJQLZ5VCZ7563F56WQ2/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YCH34NDTJQLZ5VCZ7563F56WQ2/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YCH34NDTJQLZ5VCZ7563F56WQ2/action/storage_attestation","attest_author":"https://pith.science/pith/YCH34NDTJQLZ5VCZ7563F56WQ2/action/author_attestation","sign_citation":"https://pith.science/pith/YCH34NDTJQLZ5VCZ7563F56WQ2/action/citation_signature","submit_replication":"https://pith.science/pith/YCH34NDTJQLZ5VCZ7563F56WQ2/action/replication_record"}},"created_at":"2026-05-18T00:46:54.856207+00:00","updated_at":"2026-05-18T00:46:54.856207+00:00"}