{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:MQELVSAEDPVPUVSPXW3AC43IWI","short_pith_number":"pith:MQELVSAE","canonical_record":{"source":{"id":"1908.04710","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-13T15:52:31Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a9ef1fe9484647a460ba068df0c46d58a6f3b9c70585cf02623a7eff67ba6967","abstract_canon_sha256":"c490c0b0ea800384a269035dcad275e6a1ef7b1a720408fec22bcfc9dc0149d2"},"schema_version":"1.0"},"canonical_sha256":"6408bac8041beafa564fbdb6017368b20e36a0f40ddc6879306b5e37223f2e96","source":{"kind":"arxiv","id":"1908.04710","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.04710","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"arxiv_version","alias_value":"1908.04710v3","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.04710","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_12","alias_value":"MQELVSAEDPVP","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_16","alias_value":"MQELVSAEDPVPUVSP","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_8","alias_value":"MQELVSAE","created_at":"2026-07-05T01:22:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:MQELVSAEDPVPUVSPXW3AC43IWI","target":"record","payload":{"canonical_record":{"source":{"id":"1908.04710","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-13T15:52:31Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"a9ef1fe9484647a460ba068df0c46d58a6f3b9c70585cf02623a7eff67ba6967","abstract_canon_sha256":"c490c0b0ea800384a269035dcad275e6a1ef7b1a720408fec22bcfc9dc0149d2"},"schema_version":"1.0"},"canonical_sha256":"6408bac8041beafa564fbdb6017368b20e36a0f40ddc6879306b5e37223f2e96","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:22:14.342323Z","signature_b64":"nfyPDSQW556A4Xs7uSOfFkbJOP3KCFkAiKDBVxrf6C2C0q0SKlIdRAboTsN9t75Qv+xxyhN2aPg6azjJEIpvDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6408bac8041beafa564fbdb6017368b20e36a0f40ddc6879306b5e37223f2e96","last_reissued_at":"2026-07-05T01:22:14.341858Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:22:14.341858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.04710","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":"2026-07-05T01:22:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4W6qpdZUZaTpWnXSXiwO7qzazoi0vUir/PXyjc409267besWgYoYPwbOU+kG4UiaQy44xI3Bn9oS0PH6RMb0Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:41:18.662727Z"},"content_sha256":"bd75a8fbf7a80ea5eb45b4a99d5ba32332b3d627cc4314edb3074a364bbeee88","schema_version":"1.0","event_id":"sha256:bd75a8fbf7a80ea5eb45b4a99d5ba32332b3d627cc4314edb3074a364bbeee88"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:MQELVSAEDPVPUVSPXW3AC43IWI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"metric-learn: Metric Learning Algorithms in Python","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Aur\\'elien Bellet, CJ Carey, Nathalie Vauquier, William de Vazelhes, Yuan Tang","submitted_at":"2019-08-13T15:52:31Z","abstract_excerpt":"metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms. As part of scikit-learn-contrib, it provides a unified interface compatible with scikit-learn which allows to easily perform cross-validation, model selection, and pipelining with other machine learning estimators. metric-learn is thoroughly tested and available on PyPi under the MIT licence."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.04710","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.04710/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T01:22:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RyHIHgDA7bU1beQFCHuCU33wQfzQsBs50raukhWk8fAPPrtr6chfk9BImvTEik3vpdArTaep2p1X8cT3rItSDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:41:18.663571Z"},"content_sha256":"d9b8bafa759c5f1d1b6a48b8e699cd10a8ef00cd3f3484dd6f973e8204bb59c8","schema_version":"1.0","event_id":"sha256:d9b8bafa759c5f1d1b6a48b8e699cd10a8ef00cd3f3484dd6f973e8204bb59c8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MQELVSAEDPVPUVSPXW3AC43IWI/bundle.json","state_url":"https://pith.science/pith/MQELVSAEDPVPUVSPXW3AC43IWI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MQELVSAEDPVPUVSPXW3AC43IWI/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":"2026-08-14T06:41:18Z","links":{"resolver":"https://pith.science/pith/MQELVSAEDPVPUVSPXW3AC43IWI","bundle":"https://pith.science/pith/MQELVSAEDPVPUVSPXW3AC43IWI/bundle.json","state":"https://pith.science/pith/MQELVSAEDPVPUVSPXW3AC43IWI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MQELVSAEDPVPUVSPXW3AC43IWI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:MQELVSAEDPVPUVSPXW3AC43IWI","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":"c490c0b0ea800384a269035dcad275e6a1ef7b1a720408fec22bcfc9dc0149d2","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-13T15:52:31Z","title_canon_sha256":"a9ef1fe9484647a460ba068df0c46d58a6f3b9c70585cf02623a7eff67ba6967"},"schema_version":"1.0","source":{"id":"1908.04710","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.04710","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"arxiv_version","alias_value":"1908.04710v3","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.04710","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_12","alias_value":"MQELVSAEDPVP","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_16","alias_value":"MQELVSAEDPVPUVSP","created_at":"2026-07-05T01:22:14Z"},{"alias_kind":"pith_short_8","alias_value":"MQELVSAE","created_at":"2026-07-05T01:22:14Z"}],"graph_snapshots":[{"event_id":"sha256:d9b8bafa759c5f1d1b6a48b8e699cd10a8ef00cd3f3484dd6f973e8204bb59c8","target":"graph","created_at":"2026-07-05T01:22:14Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1908.04710/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"metric-learn is an open source Python package implementing supervised and weakly-supervised distance metric learning algorithms. As part of scikit-learn-contrib, it provides a unified interface compatible with scikit-learn which allows to easily perform cross-validation, model selection, and pipelining with other machine learning estimators. metric-learn is thoroughly tested and available on PyPi under the MIT licence.","authors_text":"Aur\\'elien Bellet, CJ Carey, Nathalie Vauquier, William de Vazelhes, Yuan Tang","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-13T15:52:31Z","title":"metric-learn: Metric Learning Algorithms in Python"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.04710","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:bd75a8fbf7a80ea5eb45b4a99d5ba32332b3d627cc4314edb3074a364bbeee88","target":"record","created_at":"2026-07-05T01:22:14Z","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":"c490c0b0ea800384a269035dcad275e6a1ef7b1a720408fec22bcfc9dc0149d2","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-13T15:52:31Z","title_canon_sha256":"a9ef1fe9484647a460ba068df0c46d58a6f3b9c70585cf02623a7eff67ba6967"},"schema_version":"1.0","source":{"id":"1908.04710","kind":"arxiv","version":3}},"canonical_sha256":"6408bac8041beafa564fbdb6017368b20e36a0f40ddc6879306b5e37223f2e96","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6408bac8041beafa564fbdb6017368b20e36a0f40ddc6879306b5e37223f2e96","first_computed_at":"2026-07-05T01:22:14.341858Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:22:14.341858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nfyPDSQW556A4Xs7uSOfFkbJOP3KCFkAiKDBVxrf6C2C0q0SKlIdRAboTsN9t75Qv+xxyhN2aPg6azjJEIpvDw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:22:14.342323Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.04710","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bd75a8fbf7a80ea5eb45b4a99d5ba32332b3d627cc4314edb3074a364bbeee88","sha256:d9b8bafa759c5f1d1b6a48b8e699cd10a8ef00cd3f3484dd6f973e8204bb59c8"],"state_sha256":"49780a8e0498a5c8aa4703868ba3efb3c75c2c39fd314d5e81e383f300cf8632"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vqbp8Z5M8ovKBAs2aTmc7WcDDyY0HOD6dkw009iJEs7flkRSVbs/zgE/F6TlKOenFe9gLQOxRVVuXMaq7c0cAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T06:41:18.680083Z","bundle_sha256":"989591718e8a68a87e3f9167db208c50cb671125b7a241371e8f745bf7c68424"}}