{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:ZHZC6HAF7IPODWQLDQNM3FR7KX","short_pith_number":"pith:ZHZC6HAF","canonical_record":{"source":{"id":"1811.05530","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-13T21:11:55Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"23deedf292925c082d7b4663635dfcf2b816497705c071cf09ff5290e31e3605","abstract_canon_sha256":"e49094193892d6608cf4d63667cc3b0525f5b0f576266eade325da262d472402"},"schema_version":"1.0"},"canonical_sha256":"c9f22f1c05fa1ee1da0b1c1acd963f55d9acfb31f14296483346b8f749c96d33","source":{"kind":"arxiv","id":"1811.05530","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.05530","created_at":"2026-05-18T00:00:42Z"},{"alias_kind":"arxiv_version","alias_value":"1811.05530v1","created_at":"2026-05-18T00:00:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.05530","created_at":"2026-05-18T00:00:42Z"},{"alias_kind":"pith_short_12","alias_value":"ZHZC6HAF7IPO","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZHZC6HAF7IPODWQL","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZHZC6HAF","created_at":"2026-05-18T12:33:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:ZHZC6HAF7IPODWQLDQNM3FR7KX","target":"record","payload":{"canonical_record":{"source":{"id":"1811.05530","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-13T21:11:55Z","cross_cats_sorted":["stat.TH"],"title_canon_sha256":"23deedf292925c082d7b4663635dfcf2b816497705c071cf09ff5290e31e3605","abstract_canon_sha256":"e49094193892d6608cf4d63667cc3b0525f5b0f576266eade325da262d472402"},"schema_version":"1.0"},"canonical_sha256":"c9f22f1c05fa1ee1da0b1c1acd963f55d9acfb31f14296483346b8f749c96d33","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:42.715051Z","signature_b64":"sy5DPpNk9g5HgE+2Kx7OmKd00mYZlh9co7PccIVf3QzPhlLy20ItYQSUJbFS/aMOLsVfUVWGmT7q5lwpUgcjAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c9f22f1c05fa1ee1da0b1c1acd963f55d9acfb31f14296483346b8f749c96d33","last_reissued_at":"2026-05-18T00:00:42.714514Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:42.714514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.05530","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:00:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HPrmB2wxyt0HbU+peuYJK+omSfSUJvICD7ZTyAvzaEGYY9Yew9mk1+pjHxlOEN9liMrAF33QepiskLdERv/mDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T02:11:10.425186Z"},"content_sha256":"15211cd37fe51308fe56327998a2c2660cefa17dc3281388424b26262fb555ec","schema_version":"1.0","event_id":"sha256:15211cd37fe51308fe56327998a2c2660cefa17dc3281388424b26262fb555ec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:ZHZC6HAF7IPODWQLDQNM3FR7KX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Characterising Bayesian Network Models under Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.TH"],"primary_cat":"math.ST","authors_text":"Angelos P. Armen, Robin J. Evans","submitted_at":"2018-11-13T21:11:55Z","abstract_excerpt":"Real-life statistical samples are often plagued by selection bias, which complicates drawing conclusions about the general population. When learning causal relationships between the variables is of interest, the sample may be assumed to be from a distribution in a causal Bayesian network (BN) model under selection. Understanding the constraints in the model under selection is the first step towards recovering causal structure in the original model. The conditional-independence (CI) constraints in a BN model under selection have been already characterised; there exist, however, additional, non-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.05530","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:00:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"74mYmr+cecFnKr8gZVerl3VopmCAOxJHCHIPs9q6VMPNkwJR2abIdaxOSwfRISLBkEAes6xUCn4/GU4Z/gaSAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T02:11:10.425592Z"},"content_sha256":"d7cf5ea137cf8893ee1e8e04069a2f2457454f3ab0772ef2bde8baf25b615364","schema_version":"1.0","event_id":"sha256:d7cf5ea137cf8893ee1e8e04069a2f2457454f3ab0772ef2bde8baf25b615364"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZHZC6HAF7IPODWQLDQNM3FR7KX/bundle.json","state_url":"https://pith.science/pith/ZHZC6HAF7IPODWQLDQNM3FR7KX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZHZC6HAF7IPODWQLDQNM3FR7KX/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-27T02:11:10Z","links":{"resolver":"https://pith.science/pith/ZHZC6HAF7IPODWQLDQNM3FR7KX","bundle":"https://pith.science/pith/ZHZC6HAF7IPODWQLDQNM3FR7KX/bundle.json","state":"https://pith.science/pith/ZHZC6HAF7IPODWQLDQNM3FR7KX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZHZC6HAF7IPODWQLDQNM3FR7KX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:ZHZC6HAF7IPODWQLDQNM3FR7KX","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"e49094193892d6608cf4d63667cc3b0525f5b0f576266eade325da262d472402","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-13T21:11:55Z","title_canon_sha256":"23deedf292925c082d7b4663635dfcf2b816497705c071cf09ff5290e31e3605"},"schema_version":"1.0","source":{"id":"1811.05530","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.05530","created_at":"2026-05-18T00:00:42Z"},{"alias_kind":"arxiv_version","alias_value":"1811.05530v1","created_at":"2026-05-18T00:00:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.05530","created_at":"2026-05-18T00:00:42Z"},{"alias_kind":"pith_short_12","alias_value":"ZHZC6HAF7IPO","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_16","alias_value":"ZHZC6HAF7IPODWQL","created_at":"2026-05-18T12:33:07Z"},{"alias_kind":"pith_short_8","alias_value":"ZHZC6HAF","created_at":"2026-05-18T12:33:07Z"}],"graph_snapshots":[{"event_id":"sha256:d7cf5ea137cf8893ee1e8e04069a2f2457454f3ab0772ef2bde8baf25b615364","target":"graph","created_at":"2026-05-18T00:00:42Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Real-life statistical samples are often plagued by selection bias, which complicates drawing conclusions about the general population. When learning causal relationships between the variables is of interest, the sample may be assumed to be from a distribution in a causal Bayesian network (BN) model under selection. Understanding the constraints in the model under selection is the first step towards recovering causal structure in the original model. The conditional-independence (CI) constraints in a BN model under selection have been already characterised; there exist, however, additional, non-","authors_text":"Angelos P. Armen, Robin J. Evans","cross_cats":["stat.TH"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-13T21:11:55Z","title":"Towards Characterising Bayesian Network Models under Selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.05530","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:15211cd37fe51308fe56327998a2c2660cefa17dc3281388424b26262fb555ec","target":"record","created_at":"2026-05-18T00:00:42Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"e49094193892d6608cf4d63667cc3b0525f5b0f576266eade325da262d472402","cross_cats_sorted":["stat.TH"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.ST","submitted_at":"2018-11-13T21:11:55Z","title_canon_sha256":"23deedf292925c082d7b4663635dfcf2b816497705c071cf09ff5290e31e3605"},"schema_version":"1.0","source":{"id":"1811.05530","kind":"arxiv","version":1}},"canonical_sha256":"c9f22f1c05fa1ee1da0b1c1acd963f55d9acfb31f14296483346b8f749c96d33","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c9f22f1c05fa1ee1da0b1c1acd963f55d9acfb31f14296483346b8f749c96d33","first_computed_at":"2026-05-18T00:00:42.714514Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:42.714514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sy5DPpNk9g5HgE+2Kx7OmKd00mYZlh9co7PccIVf3QzPhlLy20ItYQSUJbFS/aMOLsVfUVWGmT7q5lwpUgcjAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:42.715051Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.05530","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:15211cd37fe51308fe56327998a2c2660cefa17dc3281388424b26262fb555ec","sha256:d7cf5ea137cf8893ee1e8e04069a2f2457454f3ab0772ef2bde8baf25b615364"],"state_sha256":"d6e71157d0d0003fed28f6d2f22e54b70f629cdb1a4be33d98a2b301fa017634"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DbGTFf1KVxdt2pZM0HcacEO3DEdHhRtjLx3rrX2otWICqW5XAHfFhWIWI7WbP+Ulo9s4Vwh29ZR5Q2vAxIgLAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T02:11:10.428078Z","bundle_sha256":"140a00272271d31be9bd133ec77bc8a7a03f322240b97074e65353e310dce9d0"}}