{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:R6TQC27GAETQAM3EZH5TXJJYCC","short_pith_number":"pith:R6TQC27G","canonical_record":{"source":{"id":"1809.08568","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-09-23T09:57:14Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"f6ae3780a3d5d4917e68512a70c95b9edaeae6122ff2c3ee0a1e4fc5a10d4f8e","abstract_canon_sha256":"03122be77046c459c699c463fa38768505808846b7be6128af664e4ffe24601f"},"schema_version":"1.0"},"canonical_sha256":"8fa7016be60127003364c9fb3ba53810a0dfb4f73f7a06e7ab2b75c38a405bd5","source":{"kind":"arxiv","id":"1809.08568","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.08568","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"arxiv_version","alias_value":"1809.08568v3","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.08568","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"pith_short_12","alias_value":"R6TQC27GAETQ","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"R6TQC27GAETQAM3E","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"R6TQC27G","created_at":"2026-05-18T12:32:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:R6TQC27GAETQAM3EZH5TXJJYCC","target":"record","payload":{"canonical_record":{"source":{"id":"1809.08568","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-09-23T09:57:14Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"f6ae3780a3d5d4917e68512a70c95b9edaeae6122ff2c3ee0a1e4fc5a10d4f8e","abstract_canon_sha256":"03122be77046c459c699c463fa38768505808846b7be6128af664e4ffe24601f"},"schema_version":"1.0"},"canonical_sha256":"8fa7016be60127003364c9fb3ba53810a0dfb4f73f7a06e7ab2b75c38a405bd5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:01:06.737016Z","signature_b64":"5J6ftgMVfPvub/jJ1QxTyAWHVODYnJvvqXvM2aNm1WoJMDlDik0Z6HUClzNhPQYlRd4Z9tWrhRIR6s2497+IDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8fa7016be60127003364c9fb3ba53810a0dfb4f73f7a06e7ab2b75c38a405bd5","last_reissued_at":"2026-05-18T00:01:06.736496Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:01:06.736496Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.08568","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:01:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"om1e204ow4E210ys3+e6fv7VGbh2VIcXU2qgxiXuPNJ+LA3CGRaU+FotsDcNKnV+PT0uUiAWyYzr9wYUqbU9Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T01:45:55.610896Z"},"content_sha256":"5de244ec066ec6ee27bbc028d980a9438bfb927e2dcbbd0baf2556e42fa2e1e0","schema_version":"1.0","event_id":"sha256:5de244ec066ec6ee27bbc028d980a9438bfb927e2dcbbd0baf2556e42fa2e1e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:R6TQC27GAETQAM3EZH5TXJJYCC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"stat.ML","authors_text":"Laiwan Chan, Shoubo Hu, Vahid Partovi Nia, Yanhui Geng, Zhitang Chen","submitted_at":"2018-09-23T09:57:14Z","abstract_excerpt":"The inference of the causal relationship between a pair of observed variables is a fundamental problem in science, and most existing approaches are based on one single causal model. In practice, however, observations are often collected from multiple sources with heterogeneous causal models due to certain uncontrollable factors, which renders causal analysis results obtained by a single model skeptical. In this paper, we generalize the Additive Noise Model (ANM) to a mixture model, which consists of a finite number of ANMs, and provide the condition of its causal identifiability. To conduct mo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.08568","kind":"arxiv","version":3},"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":"2026-05-18T00:01:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Foov1Ywtl6W9TpjDRgpwXh5iZJ7uOo5WktpbXZwvK/KMdKhxMOn7rvouXPGT6GhrJu6nh5qdEOT3EDY0tok2Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T01:45:55.611247Z"},"content_sha256":"40bc8ba0a5c63cf61bdb49ea982164ef65e9a1b4b5a80b3f5d0ec5874201393d","schema_version":"1.0","event_id":"sha256:40bc8ba0a5c63cf61bdb49ea982164ef65e9a1b4b5a80b3f5d0ec5874201393d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/R6TQC27GAETQAM3EZH5TXJJYCC/bundle.json","state_url":"https://pith.science/pith/R6TQC27GAETQAM3EZH5TXJJYCC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/R6TQC27GAETQAM3EZH5TXJJYCC/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":"2026-06-02T01:45:55Z","links":{"resolver":"https://pith.science/pith/R6TQC27GAETQAM3EZH5TXJJYCC","bundle":"https://pith.science/pith/R6TQC27GAETQAM3EZH5TXJJYCC/bundle.json","state":"https://pith.science/pith/R6TQC27GAETQAM3EZH5TXJJYCC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/R6TQC27GAETQAM3EZH5TXJJYCC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:R6TQC27GAETQAM3EZH5TXJJYCC","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":"03122be77046c459c699c463fa38768505808846b7be6128af664e4ffe24601f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-09-23T09:57:14Z","title_canon_sha256":"f6ae3780a3d5d4917e68512a70c95b9edaeae6122ff2c3ee0a1e4fc5a10d4f8e"},"schema_version":"1.0","source":{"id":"1809.08568","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.08568","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"arxiv_version","alias_value":"1809.08568v3","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.08568","created_at":"2026-05-18T00:01:06Z"},{"alias_kind":"pith_short_12","alias_value":"R6TQC27GAETQ","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"R6TQC27GAETQAM3E","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"R6TQC27G","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:40bc8ba0a5c63cf61bdb49ea982164ef65e9a1b4b5a80b3f5d0ec5874201393d","target":"graph","created_at":"2026-05-18T00:01:06Z","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":"The inference of the causal relationship between a pair of observed variables is a fundamental problem in science, and most existing approaches are based on one single causal model. In practice, however, observations are often collected from multiple sources with heterogeneous causal models due to certain uncontrollable factors, which renders causal analysis results obtained by a single model skeptical. In this paper, we generalize the Additive Noise Model (ANM) to a mixture model, which consists of a finite number of ANMs, and provide the condition of its causal identifiability. To conduct mo","authors_text":"Laiwan Chan, Shoubo Hu, Vahid Partovi Nia, Yanhui Geng, Zhitang Chen","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-09-23T09:57:14Z","title":"Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.08568","kind":"arxiv","version":3},"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":"sha256:5de244ec066ec6ee27bbc028d980a9438bfb927e2dcbbd0baf2556e42fa2e1e0","target":"record","created_at":"2026-05-18T00:01:06Z","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":"03122be77046c459c699c463fa38768505808846b7be6128af664e4ffe24601f","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2018-09-23T09:57:14Z","title_canon_sha256":"f6ae3780a3d5d4917e68512a70c95b9edaeae6122ff2c3ee0a1e4fc5a10d4f8e"},"schema_version":"1.0","source":{"id":"1809.08568","kind":"arxiv","version":3}},"canonical_sha256":"8fa7016be60127003364c9fb3ba53810a0dfb4f73f7a06e7ab2b75c38a405bd5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8fa7016be60127003364c9fb3ba53810a0dfb4f73f7a06e7ab2b75c38a405bd5","first_computed_at":"2026-05-18T00:01:06.736496Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:01:06.736496Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5J6ftgMVfPvub/jJ1QxTyAWHVODYnJvvqXvM2aNm1WoJMDlDik0Z6HUClzNhPQYlRd4Z9tWrhRIR6s2497+IDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:01:06.737016Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.08568","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5de244ec066ec6ee27bbc028d980a9438bfb927e2dcbbd0baf2556e42fa2e1e0","sha256:40bc8ba0a5c63cf61bdb49ea982164ef65e9a1b4b5a80b3f5d0ec5874201393d"],"state_sha256":"c68913e58ed7f828e02944c1ca6741a871e9a525e47d2595cf1d6ffa3c092d93"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1kYpuqRZm/qXkwvgjM17y1DvsrWJ8scW7f6/319/yx7fS7fx1AnkaZg3i1gaT07b6EikrzXARHfbjtunrarlCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T01:45:55.613104Z","bundle_sha256":"8ece826b6cc75b152cf6e8b0246f9bb5a5ad1caa04a3de300cd4c019e4773065"}}