{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:BG62MUQHDATVXKR3PJN2KCEG3O","short_pith_number":"pith:BG62MUQH","canonical_record":{"source":{"id":"1205.4174","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2012-05-18T15:12:01Z","cross_cats_sorted":["cs.DM"],"title_canon_sha256":"6c5926e26a9c946fb6123f1189fb99de1a833753224848d9a42ae2268254daad","abstract_canon_sha256":"d2e4438f929783ac0eea2ec434264ec7704bc338a4b1ec93ff19e70f56adbcc8"},"schema_version":"1.0"},"canonical_sha256":"09bda6520718275baa3b7a5ba50886db9d5a3b6e6efcaaedf0bee60cffbf5c91","source":{"kind":"arxiv","id":"1205.4174","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1205.4174","created_at":"2026-05-18T02:50:43Z"},{"alias_kind":"arxiv_version","alias_value":"1205.4174v3","created_at":"2026-05-18T02:50:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.4174","created_at":"2026-05-18T02:50:43Z"},{"alias_kind":"pith_short_12","alias_value":"BG62MUQHDATV","created_at":"2026-05-18T12:26:58Z"},{"alias_kind":"pith_short_16","alias_value":"BG62MUQHDATVXKR3","created_at":"2026-05-18T12:26:58Z"},{"alias_kind":"pith_short_8","alias_value":"BG62MUQH","created_at":"2026-05-18T12:26:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:BG62MUQHDATVXKR3PJN2KCEG3O","target":"record","payload":{"canonical_record":{"source":{"id":"1205.4174","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2012-05-18T15:12:01Z","cross_cats_sorted":["cs.DM"],"title_canon_sha256":"6c5926e26a9c946fb6123f1189fb99de1a833753224848d9a42ae2268254daad","abstract_canon_sha256":"d2e4438f929783ac0eea2ec434264ec7704bc338a4b1ec93ff19e70f56adbcc8"},"schema_version":"1.0"},"canonical_sha256":"09bda6520718275baa3b7a5ba50886db9d5a3b6e6efcaaedf0bee60cffbf5c91","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:50:43.365082Z","signature_b64":"LnsHiCyS3AJJSVg+j/Y1Rm+qKbYxhtyrTRLZ/a8cHcmScV2Ka2aNrDllCyQofG/xzt+pa5Jiqv+sTHpee4LTAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"09bda6520718275baa3b7a5ba50886db9d5a3b6e6efcaaedf0bee60cffbf5c91","last_reissued_at":"2026-05-18T02:50:43.364558Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:50:43.364558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1205.4174","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":"2026-05-18T02:50:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UyQZ2KGuIL628slbqPWh3qE2X4JBHugEScXBYQY0hIOsQJlQI2kR0g7UUaTpIhXpzOk2OJBSrSm62OX77l+AAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T05:51:33.390904Z"},"content_sha256":"38c80c840a18ced6eb4cb096938f900215649f7daf22dcf458f5c328e043c513","schema_version":"1.0","event_id":"sha256:38c80c840a18ced6eb4cb096938f900215649f7daf22dcf458f5c328e043c513"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:BG62MUQHDATVXKR3PJN2KCEG3O","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Two Optimal Strategies for Active Learning of Causal Models from Interventional Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DM"],"primary_cat":"stat.ME","authors_text":"Alain Hauser, Peter B\\\"uhlmann","submitted_at":"2012-05-18T15:12:01Z","abstract_excerpt":"From observational data alone, a causal DAG is only identifiable up to Markov equivalence. Interventional data generally improves identifiability; however, the gain of an intervention strongly depends on the intervention target, that is, the intervened variables. We present active learning (that is, optimal experimental design) strategies calculating optimal interventions for two different learning goals. The first one is a greedy approach using single-vertex interventions that maximizes the number of edges that can be oriented after each intervention. The second one yields in polynomial time "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.4174","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":"2026-05-18T02:50:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X6GPKxxWcsElcWiPoxK/PjxaQZsD1ZJVAMjBYeHcngl/mconZyXsTYb+erG1iK3OjjvT7RkF/TTLv7oLnglNDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T05:51:33.391726Z"},"content_sha256":"e21d24c712062f3fc949f8d8a86f77bb82acdabb30f70ef1f9d8091c00eadfd9","schema_version":"1.0","event_id":"sha256:e21d24c712062f3fc949f8d8a86f77bb82acdabb30f70ef1f9d8091c00eadfd9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BG62MUQHDATVXKR3PJN2KCEG3O/bundle.json","state_url":"https://pith.science/pith/BG62MUQHDATVXKR3PJN2KCEG3O/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BG62MUQHDATVXKR3PJN2KCEG3O/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":"2026-06-10T05:51:33Z","links":{"resolver":"https://pith.science/pith/BG62MUQHDATVXKR3PJN2KCEG3O","bundle":"https://pith.science/pith/BG62MUQHDATVXKR3PJN2KCEG3O/bundle.json","state":"https://pith.science/pith/BG62MUQHDATVXKR3PJN2KCEG3O/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BG62MUQHDATVXKR3PJN2KCEG3O/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:BG62MUQHDATVXKR3PJN2KCEG3O","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":"d2e4438f929783ac0eea2ec434264ec7704bc338a4b1ec93ff19e70f56adbcc8","cross_cats_sorted":["cs.DM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2012-05-18T15:12:01Z","title_canon_sha256":"6c5926e26a9c946fb6123f1189fb99de1a833753224848d9a42ae2268254daad"},"schema_version":"1.0","source":{"id":"1205.4174","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1205.4174","created_at":"2026-05-18T02:50:43Z"},{"alias_kind":"arxiv_version","alias_value":"1205.4174v3","created_at":"2026-05-18T02:50:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1205.4174","created_at":"2026-05-18T02:50:43Z"},{"alias_kind":"pith_short_12","alias_value":"BG62MUQHDATV","created_at":"2026-05-18T12:26:58Z"},{"alias_kind":"pith_short_16","alias_value":"BG62MUQHDATVXKR3","created_at":"2026-05-18T12:26:58Z"},{"alias_kind":"pith_short_8","alias_value":"BG62MUQH","created_at":"2026-05-18T12:26:58Z"}],"graph_snapshots":[{"event_id":"sha256:e21d24c712062f3fc949f8d8a86f77bb82acdabb30f70ef1f9d8091c00eadfd9","target":"graph","created_at":"2026-05-18T02:50:43Z","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":"From observational data alone, a causal DAG is only identifiable up to Markov equivalence. Interventional data generally improves identifiability; however, the gain of an intervention strongly depends on the intervention target, that is, the intervened variables. We present active learning (that is, optimal experimental design) strategies calculating optimal interventions for two different learning goals. The first one is a greedy approach using single-vertex interventions that maximizes the number of edges that can be oriented after each intervention. The second one yields in polynomial time ","authors_text":"Alain Hauser, Peter B\\\"uhlmann","cross_cats":["cs.DM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2012-05-18T15:12:01Z","title":"Two Optimal Strategies for Active Learning of Causal Models from Interventional Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1205.4174","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":"sha256:38c80c840a18ced6eb4cb096938f900215649f7daf22dcf458f5c328e043c513","target":"record","created_at":"2026-05-18T02:50:43Z","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":"d2e4438f929783ac0eea2ec434264ec7704bc338a4b1ec93ff19e70f56adbcc8","cross_cats_sorted":["cs.DM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2012-05-18T15:12:01Z","title_canon_sha256":"6c5926e26a9c946fb6123f1189fb99de1a833753224848d9a42ae2268254daad"},"schema_version":"1.0","source":{"id":"1205.4174","kind":"arxiv","version":3}},"canonical_sha256":"09bda6520718275baa3b7a5ba50886db9d5a3b6e6efcaaedf0bee60cffbf5c91","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"09bda6520718275baa3b7a5ba50886db9d5a3b6e6efcaaedf0bee60cffbf5c91","first_computed_at":"2026-05-18T02:50:43.364558Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:50:43.364558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LnsHiCyS3AJJSVg+j/Y1Rm+qKbYxhtyrTRLZ/a8cHcmScV2Ka2aNrDllCyQofG/xzt+pa5Jiqv+sTHpee4LTAA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:50:43.365082Z","signed_message":"canonical_sha256_bytes"},"source_id":"1205.4174","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:38c80c840a18ced6eb4cb096938f900215649f7daf22dcf458f5c328e043c513","sha256:e21d24c712062f3fc949f8d8a86f77bb82acdabb30f70ef1f9d8091c00eadfd9"],"state_sha256":"d1464879ef596b321a1d59d61403db7ccb501a7655b210be0b0092bccbb10565"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4UJqqVrBrCwJNgZslyXReJ2LxH6Zuj83Jlh9XRurNR9rrAbwB8nNGj9BBIt4OVJlXmix20HtxH7vFZ7lwferBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T05:51:33.395823Z","bundle_sha256":"63eef483fe18b716e971de0ffee1345081731bf8600949a8b36202fc13b097b8"}}