{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:X6AQMFDLQYJO6Y3T7NHZOSQGRX","short_pith_number":"pith:X6AQMFDL","canonical_record":{"source":{"id":"1506.07669","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-06-25T08:59:23Z","cross_cats_sorted":[],"title_canon_sha256":"3b4754936daeff23d8490d4c48015d250a62623536f77df4631197439800bbdd","abstract_canon_sha256":"9fb389134163b98dfa0588b1bef245a6b6375195720f2c08356960c97d4fa810"},"schema_version":"1.0"},"canonical_sha256":"bf8106146b8612ef6373fb4f974a068de2e114ac7202293f9010ab809cce35c0","source":{"kind":"arxiv","id":"1506.07669","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1506.07669","created_at":"2026-05-18T01:38:51Z"},{"alias_kind":"arxiv_version","alias_value":"1506.07669v1","created_at":"2026-05-18T01:38:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1506.07669","created_at":"2026-05-18T01:38:51Z"},{"alias_kind":"pith_short_12","alias_value":"X6AQMFDLQYJO","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"X6AQMFDLQYJO6Y3T","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"X6AQMFDL","created_at":"2026-05-18T12:29:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:X6AQMFDLQYJO6Y3T7NHZOSQGRX","target":"record","payload":{"canonical_record":{"source":{"id":"1506.07669","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-06-25T08:59:23Z","cross_cats_sorted":[],"title_canon_sha256":"3b4754936daeff23d8490d4c48015d250a62623536f77df4631197439800bbdd","abstract_canon_sha256":"9fb389134163b98dfa0588b1bef245a6b6375195720f2c08356960c97d4fa810"},"schema_version":"1.0"},"canonical_sha256":"bf8106146b8612ef6373fb4f974a068de2e114ac7202293f9010ab809cce35c0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:38:51.159868Z","signature_b64":"/izFMSyzSpShniz24mw4D7Oc5QkGAkJ21SIBmAN25wKaPBhVcN8ZEnbxBKHB0TrUy+L+zbbyOhf3meN1hkZuDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bf8106146b8612ef6373fb4f974a068de2e114ac7202293f9010ab809cce35c0","last_reissued_at":"2026-05-18T01:38:51.159243Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:38:51.159243Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1506.07669","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":"2026-05-18T01:38:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TQmDYxs/xh/S02nMXYQAEqkn55wPU5OGeVZ/RSQysLBfse75G4DBZlrMZZ912+rPBe7fD7tbrRltZNWbtgzXAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T20:54:23.659705Z"},"content_sha256":"fabbd80ea1761833bc3d02942fc6f4ce3ca6c8228a6a8820b723ca916ca18af0","schema_version":"1.0","event_id":"sha256:fabbd80ea1761833bc3d02942fc6f4ce3ca6c8228a6a8820b723ca916ca18af0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:X6AQMFDLQYJO6Y3T7NHZOSQGRX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A review of some recent advances in causal inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Marloes H. Maathuis, Preetam Nandy","submitted_at":"2015-06-25T08:59:23Z","abstract_excerpt":"We give a selective review of some recent developments in causal inference, intended for researchers who are not familiar with graphical models and causality, and with a focus on methods that are applicable to large data sets. We mainly address the problem of estimating causal effects from observational data. For example, one can think of estimating the effect of single or multiple gene knockouts from wild-type gene expression data, that is, from gene expression measurements that were obtained without doing any gene knockout experiments.\n  We assume that the observational data are generated fr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1506.07669","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":"2026-05-18T01:38:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qEwu6eBeQtAlFm5jbU9kYq/gV5XdBU/Kk0TSz9p/xcRcMmYhduUq4nSSgD//UO2Codo/f97n5gQ33UxyF3nwBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T20:54:23.660049Z"},"content_sha256":"6a9729d371fe9d4da6f53466e274c30e605d5cc3d58128a4e7d8643b31d2ff7c","schema_version":"1.0","event_id":"sha256:6a9729d371fe9d4da6f53466e274c30e605d5cc3d58128a4e7d8643b31d2ff7c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X6AQMFDLQYJO6Y3T7NHZOSQGRX/bundle.json","state_url":"https://pith.science/pith/X6AQMFDLQYJO6Y3T7NHZOSQGRX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X6AQMFDLQYJO6Y3T7NHZOSQGRX/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":"2026-05-27T20:54:23Z","links":{"resolver":"https://pith.science/pith/X6AQMFDLQYJO6Y3T7NHZOSQGRX","bundle":"https://pith.science/pith/X6AQMFDLQYJO6Y3T7NHZOSQGRX/bundle.json","state":"https://pith.science/pith/X6AQMFDLQYJO6Y3T7NHZOSQGRX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X6AQMFDLQYJO6Y3T7NHZOSQGRX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:X6AQMFDLQYJO6Y3T7NHZOSQGRX","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":"9fb389134163b98dfa0588b1bef245a6b6375195720f2c08356960c97d4fa810","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-06-25T08:59:23Z","title_canon_sha256":"3b4754936daeff23d8490d4c48015d250a62623536f77df4631197439800bbdd"},"schema_version":"1.0","source":{"id":"1506.07669","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1506.07669","created_at":"2026-05-18T01:38:51Z"},{"alias_kind":"arxiv_version","alias_value":"1506.07669v1","created_at":"2026-05-18T01:38:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1506.07669","created_at":"2026-05-18T01:38:51Z"},{"alias_kind":"pith_short_12","alias_value":"X6AQMFDLQYJO","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_16","alias_value":"X6AQMFDLQYJO6Y3T","created_at":"2026-05-18T12:29:47Z"},{"alias_kind":"pith_short_8","alias_value":"X6AQMFDL","created_at":"2026-05-18T12:29:47Z"}],"graph_snapshots":[{"event_id":"sha256:6a9729d371fe9d4da6f53466e274c30e605d5cc3d58128a4e7d8643b31d2ff7c","target":"graph","created_at":"2026-05-18T01:38:51Z","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":"We give a selective review of some recent developments in causal inference, intended for researchers who are not familiar with graphical models and causality, and with a focus on methods that are applicable to large data sets. We mainly address the problem of estimating causal effects from observational data. For example, one can think of estimating the effect of single or multiple gene knockouts from wild-type gene expression data, that is, from gene expression measurements that were obtained without doing any gene knockout experiments.\n  We assume that the observational data are generated fr","authors_text":"Marloes H. Maathuis, Preetam Nandy","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-06-25T08:59:23Z","title":"A review of some recent advances in causal inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1506.07669","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:fabbd80ea1761833bc3d02942fc6f4ce3ca6c8228a6a8820b723ca916ca18af0","target":"record","created_at":"2026-05-18T01:38:51Z","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":"9fb389134163b98dfa0588b1bef245a6b6375195720f2c08356960c97d4fa810","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2015-06-25T08:59:23Z","title_canon_sha256":"3b4754936daeff23d8490d4c48015d250a62623536f77df4631197439800bbdd"},"schema_version":"1.0","source":{"id":"1506.07669","kind":"arxiv","version":1}},"canonical_sha256":"bf8106146b8612ef6373fb4f974a068de2e114ac7202293f9010ab809cce35c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bf8106146b8612ef6373fb4f974a068de2e114ac7202293f9010ab809cce35c0","first_computed_at":"2026-05-18T01:38:51.159243Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:38:51.159243Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/izFMSyzSpShniz24mw4D7Oc5QkGAkJ21SIBmAN25wKaPBhVcN8ZEnbxBKHB0TrUy+L+zbbyOhf3meN1hkZuDA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:38:51.159868Z","signed_message":"canonical_sha256_bytes"},"source_id":"1506.07669","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fabbd80ea1761833bc3d02942fc6f4ce3ca6c8228a6a8820b723ca916ca18af0","sha256:6a9729d371fe9d4da6f53466e274c30e605d5cc3d58128a4e7d8643b31d2ff7c"],"state_sha256":"482e99a985ef48f2964e8c35fab4cead915f166ae8fa14bde497ab440db6ed32"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tWzXeUIcdSc/qFN8AO3prP1LhkTVNbqvF6BsPN/L5+/SFSg48VS8X9Z2pgSSN5XrfzPYCdqF4jMxHXzgVegWCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T20:54:23.662954Z","bundle_sha256":"3bdebd84bc6f806f5a9a7f4d6fa234f0428ccf889fec78bd3d7a85eb6614be18"}}