{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2012:KXMW2KXITQNPIBZYM2LTZVLLNE","short_pith_number":"pith:KXMW2KXI","schema_version":"1.0","canonical_sha256":"55d96d2ae89c1af4073866973cd56b692220093d51fac3b6ffc9217d7e81bb7a","source":{"kind":"arxiv","id":"1205.2641","version":1},"attestation_state":"computed","paper":{"title":"Bayesian Discovery of Linear Acyclic Causal Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ME"],"primary_cat":"stat.ML","authors_text":"Antti Hyttinen, Patrik O. Hoyer","submitted_at":"2012-05-09T15:30:07Z","abstract_excerpt":"Methods for automated discovery of causal relationships from non-interventional data have received much attention recently. A widely used and well understood model family is given by linear acyclic causal models (recursive structural equation models). For Gaussian data both constraint-based methods (Spirtes et al., 1993; Pearl, 2000) (which output a single equivalence class) and Bayesian score-based methods (Geiger and Heckerman, 1994) (which assign relative scores to the equivalence classes) are available. On the contrary, all current methods able to utilize non-Gaussianity in the data (Shimi"},"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":"1205.2641","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2012-05-09T15:30:07Z","cross_cats_sorted":["cs.LG","stat.ME"],"title_canon_sha256":"0485491ceaadab787f59b3a3000432fa8a2bc3a764d02710e8928bb504f7ce47","abstract_canon_sha256":"ee7f53ea4fb52356309f9496286f00eb0c627a1403e816ef3c584b5d663e91f3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:55:47.696190Z","signature_b64":"xKjB0sonPynC+dLhSA2PQfup8s6XplPxXMWH7dLMbGql9OL+KHEoL7HnOpA1Z5yADrccdPrO5K9TI3XtR3sDBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"55d96d2ae89c1af4073866973cd56b692220093d51fac3b6ffc9217d7e81bb7a","last_reissued_at":"2026-05-18T03:55:47.695568Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:55:47.695568Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bayesian Discovery of Linear Acyclic Causal Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ME"],"primary_cat":"stat.ML","authors_text":"Antti Hyttinen, Patrik O. Hoyer","submitted_at":"2012-05-09T15:30:07Z","abstract_excerpt":"Methods for automated discovery of causal relationships from non-interventional data have received much attention recently. A widely used and well understood model family is given by linear acyclic causal models (recursive structural equation models). For Gaussian data both constraint-based methods (Spirtes et al., 1993; Pearl, 2000) (which output a single equivalence class) and Bayesian score-based methods (Geiger and Heckerman, 1994) (which assign relative scores to the equivalence classes) are available. On the contrary, all current methods able to utilize non-Gaussianity in the data (Shimi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.2641","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":"1205.2641","created_at":"2026-05-18T03:55:47.695676+00:00"},{"alias_kind":"arxiv_version","alias_value":"1205.2641v1","created_at":"2026-05-18T03:55:47.695676+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.2641","created_at":"2026-05-18T03:55:47.695676+00:00"},{"alias_kind":"pith_short_12","alias_value":"KXMW2KXITQNP","created_at":"2026-05-18T12:27:11.947152+00:00"},{"alias_kind":"pith_short_16","alias_value":"KXMW2KXITQNPIBZY","created_at":"2026-05-18T12:27:11.947152+00:00"},{"alias_kind":"pith_short_8","alias_value":"KXMW2KXI","created_at":"2026-05-18T12:27:11.947152+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/KXMW2KXITQNPIBZYM2LTZVLLNE","json":"https://pith.science/pith/KXMW2KXITQNPIBZYM2LTZVLLNE.json","graph_json":"https://pith.science/api/pith-number/KXMW2KXITQNPIBZYM2LTZVLLNE/graph.json","events_json":"https://pith.science/api/pith-number/KXMW2KXITQNPIBZYM2LTZVLLNE/events.json","paper":"https://pith.science/paper/KXMW2KXI"},"agent_actions":{"view_html":"https://pith.science/pith/KXMW2KXITQNPIBZYM2LTZVLLNE","download_json":"https://pith.science/pith/KXMW2KXITQNPIBZYM2LTZVLLNE.json","view_paper":"https://pith.science/paper/KXMW2KXI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1205.2641&json=true","fetch_graph":"https://pith.science/api/pith-number/KXMW2KXITQNPIBZYM2LTZVLLNE/graph.json","fetch_events":"https://pith.science/api/pith-number/KXMW2KXITQNPIBZYM2LTZVLLNE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KXMW2KXITQNPIBZYM2LTZVLLNE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KXMW2KXITQNPIBZYM2LTZVLLNE/action/storage_attestation","attest_author":"https://pith.science/pith/KXMW2KXITQNPIBZYM2LTZVLLNE/action/author_attestation","sign_citation":"https://pith.science/pith/KXMW2KXITQNPIBZYM2LTZVLLNE/action/citation_signature","submit_replication":"https://pith.science/pith/KXMW2KXITQNPIBZYM2LTZVLLNE/action/replication_record"}},"created_at":"2026-05-18T03:55:47.695676+00:00","updated_at":"2026-05-18T03:55:47.695676+00:00"}