{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:EM2I7363X3KOJIWPD4RFGQMHZN","short_pith_number":"pith:EM2I7363","canonical_record":{"source":{"id":"1806.06270","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-16T17:08:15Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"8c76ecb72ddfce3cfb54ed6e6ec3eccb1b0d0b3e9836e240620e03d8926087d9","abstract_canon_sha256":"31406bf764a3bf8c30fa2cd9640c7f67013f4611e33be93b0659f53688e4c8ba"},"schema_version":"1.0"},"canonical_sha256":"23348fefdbbed4e4a2cf1f22534187cb65c4e766c179acc9b148b7053df66ca0","source":{"kind":"arxiv","id":"1806.06270","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.06270","created_at":"2026-05-18T00:10:59Z"},{"alias_kind":"arxiv_version","alias_value":"1806.06270v2","created_at":"2026-05-18T00:10:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.06270","created_at":"2026-05-18T00:10:59Z"},{"alias_kind":"pith_short_12","alias_value":"EM2I7363X3KO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"EM2I7363X3KOJIWP","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"EM2I7363","created_at":"2026-05-18T12:32:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:EM2I7363X3KOJIWPD4RFGQMHZN","target":"record","payload":{"canonical_record":{"source":{"id":"1806.06270","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-16T17:08:15Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"8c76ecb72ddfce3cfb54ed6e6ec3eccb1b0d0b3e9836e240620e03d8926087d9","abstract_canon_sha256":"31406bf764a3bf8c30fa2cd9640c7f67013f4611e33be93b0659f53688e4c8ba"},"schema_version":"1.0"},"canonical_sha256":"23348fefdbbed4e4a2cf1f22534187cb65c4e766c179acc9b148b7053df66ca0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:59.391453Z","signature_b64":"G4srR4/BOYod0NuG9hKhIuU7r5zovy3yCFXEJ+hDqGoCnfi/dxQwqzdcag6Jb84HKjmnpDm5OGp+e4tWznFUBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"23348fefdbbed4e4a2cf1f22534187cb65c4e766c179acc9b148b7053df66ca0","last_reissued_at":"2026-05-18T00:10:59.390667Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:59.390667Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.06270","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:10:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PXkJVgkHzJOhHe1hUTXKOg/bwDQeUp9o1Cc7QKazYk3GPnZaElRZuj4a+DSZ6uvlNtV399Yl8gdmFeHS1VqTDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T19:42:42.628120Z"},"content_sha256":"05686f02e7501c3f4467818a9c226e75054826e498dd1121457b80d6439adce2","schema_version":"1.0","event_id":"sha256:05686f02e7501c3f4467818a9c226e75054826e498dd1121457b80d6439adce2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:EM2I7363X3KOJIWPD4RFGQMHZN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Stable Prediction across Unknown Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Bo Li, Kun Kuang, Peng Cui, Ruoxuan Xiong, Susan Athey","submitted_at":"2018-06-16T17:08:15Z","abstract_excerpt":"In many important machine learning applications, the training distribution used to learn a probabilistic classifier differs from the testing distribution on which the classifier will be used to make predictions. Traditional methods correct the distribution shift by reweighting the training data with the ratio of the density between test and training data. In many applications training takes place without prior knowledge of the testing distribution on which the algorithm will be applied in the future. Recently, methods have been proposed to address the shift by learning causal structure, but th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.06270","kind":"arxiv","version":2},"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":"2026-05-18T00:10:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+tVinfEivpszutNEqsW7JHwTatyahODpAxTB9TzT/gnNWU6uXEtLfJF4usNwDSTy2EanWo2hHwD5ZfFP4EolAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T19:42:42.628815Z"},"content_sha256":"a023d1de163b4b93849b2de0ebf24f11570f2265439495b95e4c7efa85b94e97","schema_version":"1.0","event_id":"sha256:a023d1de163b4b93849b2de0ebf24f11570f2265439495b95e4c7efa85b94e97"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EM2I7363X3KOJIWPD4RFGQMHZN/bundle.json","state_url":"https://pith.science/pith/EM2I7363X3KOJIWPD4RFGQMHZN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EM2I7363X3KOJIWPD4RFGQMHZN/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":"2026-05-25T19:42:42Z","links":{"resolver":"https://pith.science/pith/EM2I7363X3KOJIWPD4RFGQMHZN","bundle":"https://pith.science/pith/EM2I7363X3KOJIWPD4RFGQMHZN/bundle.json","state":"https://pith.science/pith/EM2I7363X3KOJIWPD4RFGQMHZN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EM2I7363X3KOJIWPD4RFGQMHZN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:EM2I7363X3KOJIWPD4RFGQMHZN","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":"31406bf764a3bf8c30fa2cd9640c7f67013f4611e33be93b0659f53688e4c8ba","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-16T17:08:15Z","title_canon_sha256":"8c76ecb72ddfce3cfb54ed6e6ec3eccb1b0d0b3e9836e240620e03d8926087d9"},"schema_version":"1.0","source":{"id":"1806.06270","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.06270","created_at":"2026-05-18T00:10:59Z"},{"alias_kind":"arxiv_version","alias_value":"1806.06270v2","created_at":"2026-05-18T00:10:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.06270","created_at":"2026-05-18T00:10:59Z"},{"alias_kind":"pith_short_12","alias_value":"EM2I7363X3KO","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_16","alias_value":"EM2I7363X3KOJIWP","created_at":"2026-05-18T12:32:22Z"},{"alias_kind":"pith_short_8","alias_value":"EM2I7363","created_at":"2026-05-18T12:32:22Z"}],"graph_snapshots":[{"event_id":"sha256:a023d1de163b4b93849b2de0ebf24f11570f2265439495b95e4c7efa85b94e97","target":"graph","created_at":"2026-05-18T00:10:59Z","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":"In many important machine learning applications, the training distribution used to learn a probabilistic classifier differs from the testing distribution on which the classifier will be used to make predictions. Traditional methods correct the distribution shift by reweighting the training data with the ratio of the density between test and training data. In many applications training takes place without prior knowledge of the testing distribution on which the algorithm will be applied in the future. Recently, methods have been proposed to address the shift by learning causal structure, but th","authors_text":"Bo Li, Kun Kuang, Peng Cui, Ruoxuan Xiong, Susan Athey","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-16T17:08:15Z","title":"Stable Prediction across Unknown Environments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.06270","kind":"arxiv","version":2},"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":"sha256:05686f02e7501c3f4467818a9c226e75054826e498dd1121457b80d6439adce2","target":"record","created_at":"2026-05-18T00:10:59Z","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":"31406bf764a3bf8c30fa2cd9640c7f67013f4611e33be93b0659f53688e4c8ba","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-16T17:08:15Z","title_canon_sha256":"8c76ecb72ddfce3cfb54ed6e6ec3eccb1b0d0b3e9836e240620e03d8926087d9"},"schema_version":"1.0","source":{"id":"1806.06270","kind":"arxiv","version":2}},"canonical_sha256":"23348fefdbbed4e4a2cf1f22534187cb65c4e766c179acc9b148b7053df66ca0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"23348fefdbbed4e4a2cf1f22534187cb65c4e766c179acc9b148b7053df66ca0","first_computed_at":"2026-05-18T00:10:59.390667Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:10:59.390667Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G4srR4/BOYod0NuG9hKhIuU7r5zovy3yCFXEJ+hDqGoCnfi/dxQwqzdcag6Jb84HKjmnpDm5OGp+e4tWznFUBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:10:59.391453Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.06270","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:05686f02e7501c3f4467818a9c226e75054826e498dd1121457b80d6439adce2","sha256:a023d1de163b4b93849b2de0ebf24f11570f2265439495b95e4c7efa85b94e97"],"state_sha256":"73ced5d10cbe59ba72d22003dfc6f1378c72e0ba876457a9f5ef1ff9f6d75f6b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tqLIrvkKgkRAm0red81VRxvUPo58OtdOuELBtRAeLKfUVP0Ty3Rr9Mf4A119n7jfUQcBGCRrb8lb/yCekKgZDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T19:42:42.632601Z","bundle_sha256":"48c431f179bbf2ecbb9acba869791a3224bac64d396530ea52a3946b0d19117c"}}