{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:NXUQAN4QSK7G4LN5VNX722BI34","short_pith_number":"pith:NXUQAN4Q","canonical_record":{"source":{"id":"1407.7644","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-07-29T07:19:08Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6f90ddbcd4189ad22260878e7ebc482962db5d97ee0ee09476444a128fe19b8c","abstract_canon_sha256":"9e2f68b0bd6d81a7dc1548263bd13ee81facaf6c9728b62fd6ae6a10792c6cb1"},"schema_version":"1.0"},"canonical_sha256":"6de900379092be6e2dbdab6ffd6828df0325e63d6efb14cc37ea26c4f4451ce8","source":{"kind":"arxiv","id":"1407.7644","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1407.7644","created_at":"2026-05-18T02:39:00Z"},{"alias_kind":"arxiv_version","alias_value":"1407.7644v2","created_at":"2026-05-18T02:39:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.7644","created_at":"2026-05-18T02:39:00Z"},{"alias_kind":"pith_short_12","alias_value":"NXUQAN4QSK7G","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"NXUQAN4QSK7G4LN5","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"NXUQAN4Q","created_at":"2026-05-18T12:28:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:NXUQAN4QSK7G4LN5VNX722BI34","target":"record","payload":{"canonical_record":{"source":{"id":"1407.7644","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-07-29T07:19:08Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6f90ddbcd4189ad22260878e7ebc482962db5d97ee0ee09476444a128fe19b8c","abstract_canon_sha256":"9e2f68b0bd6d81a7dc1548263bd13ee81facaf6c9728b62fd6ae6a10792c6cb1"},"schema_version":"1.0"},"canonical_sha256":"6de900379092be6e2dbdab6ffd6828df0325e63d6efb14cc37ea26c4f4451ce8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:39:00.769220Z","signature_b64":"508t2cgW64TD3OdeoRsSV+VzeGMgcQ+ssPr+lEILiIZftGHbZnumMCvrpKMg2mwos6OxK46TTykwntGlDwqwBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6de900379092be6e2dbdab6ffd6828df0325e63d6efb14cc37ea26c4f4451ce8","last_reissued_at":"2026-05-18T02:39:00.768580Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:39:00.768580Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1407.7644","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":"2026-05-18T02:39:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"91e5AWcmoW+FegSKZ2N1/Yal3smCKPxVKaRhWRtORnvuHEV/GVDut88OCg9jwXsK6S1YcxGTN+sYLal7xiZbAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T09:54:33.652785Z"},"content_sha256":"c8b96897532442eacdf7495076254874fc15f4462ea35fb1a06b1b3270585589","schema_version":"1.0","event_id":"sha256:c8b96897532442eacdf7495076254874fc15f4462ea35fb1a06b1b3270585589"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:NXUQAN4QSK7G4LN5VNX722BI34","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Estimating the Accuracies of Multiple Classifiers Without Labeled Data","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Ariel Jaffe, Boaz Nadler, Yuval Kluger","submitted_at":"2014-07-29T07:19:08Z","abstract_excerpt":"In various situations one is given only the predictions of multiple classifiers over a large unlabeled test data. This scenario raises the following questions: Without any labeled data and without any a-priori knowledge about the reliability of these different classifiers, is it possible to consistently and computationally efficiently estimate their accuracies? Furthermore, also in a completely unsupervised manner, can one construct a more accurate unsupervised ensemble classifier? In this paper, focusing on the binary case, we present simple, computationally efficient algorithms to solve thes"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.7644","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":"2026-05-18T02:39:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DqWXi/8SBYG0QruZyXCpJLwiJCVym3epJEn7z4mT7miutZDb5Df34bK2F18XFZ6nIuvclsyjk84nIEATUL3iDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-04T09:54:33.653128Z"},"content_sha256":"14c55b12e3e65a0d513f659fcf4a9ac32e9c725157774c9756007f19562fd0e5","schema_version":"1.0","event_id":"sha256:14c55b12e3e65a0d513f659fcf4a9ac32e9c725157774c9756007f19562fd0e5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NXUQAN4QSK7G4LN5VNX722BI34/bundle.json","state_url":"https://pith.science/pith/NXUQAN4QSK7G4LN5VNX722BI34/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NXUQAN4QSK7G4LN5VNX722BI34/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":"2026-07-04T09:54:33Z","links":{"resolver":"https://pith.science/pith/NXUQAN4QSK7G4LN5VNX722BI34","bundle":"https://pith.science/pith/NXUQAN4QSK7G4LN5VNX722BI34/bundle.json","state":"https://pith.science/pith/NXUQAN4QSK7G4LN5VNX722BI34/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NXUQAN4QSK7G4LN5VNX722BI34/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:NXUQAN4QSK7G4LN5VNX722BI34","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":"9e2f68b0bd6d81a7dc1548263bd13ee81facaf6c9728b62fd6ae6a10792c6cb1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-07-29T07:19:08Z","title_canon_sha256":"6f90ddbcd4189ad22260878e7ebc482962db5d97ee0ee09476444a128fe19b8c"},"schema_version":"1.0","source":{"id":"1407.7644","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1407.7644","created_at":"2026-05-18T02:39:00Z"},{"alias_kind":"arxiv_version","alias_value":"1407.7644v2","created_at":"2026-05-18T02:39:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1407.7644","created_at":"2026-05-18T02:39:00Z"},{"alias_kind":"pith_short_12","alias_value":"NXUQAN4QSK7G","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_16","alias_value":"NXUQAN4QSK7G4LN5","created_at":"2026-05-18T12:28:41Z"},{"alias_kind":"pith_short_8","alias_value":"NXUQAN4Q","created_at":"2026-05-18T12:28:41Z"}],"graph_snapshots":[{"event_id":"sha256:14c55b12e3e65a0d513f659fcf4a9ac32e9c725157774c9756007f19562fd0e5","target":"graph","created_at":"2026-05-18T02:39:00Z","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 various situations one is given only the predictions of multiple classifiers over a large unlabeled test data. This scenario raises the following questions: Without any labeled data and without any a-priori knowledge about the reliability of these different classifiers, is it possible to consistently and computationally efficiently estimate their accuracies? Furthermore, also in a completely unsupervised manner, can one construct a more accurate unsupervised ensemble classifier? In this paper, focusing on the binary case, we present simple, computationally efficient algorithms to solve thes","authors_text":"Ariel Jaffe, Boaz Nadler, Yuval Kluger","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-07-29T07:19:08Z","title":"Estimating the Accuracies of Multiple Classifiers Without Labeled Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1407.7644","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:c8b96897532442eacdf7495076254874fc15f4462ea35fb1a06b1b3270585589","target":"record","created_at":"2026-05-18T02:39:00Z","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":"9e2f68b0bd6d81a7dc1548263bd13ee81facaf6c9728b62fd6ae6a10792c6cb1","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2014-07-29T07:19:08Z","title_canon_sha256":"6f90ddbcd4189ad22260878e7ebc482962db5d97ee0ee09476444a128fe19b8c"},"schema_version":"1.0","source":{"id":"1407.7644","kind":"arxiv","version":2}},"canonical_sha256":"6de900379092be6e2dbdab6ffd6828df0325e63d6efb14cc37ea26c4f4451ce8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6de900379092be6e2dbdab6ffd6828df0325e63d6efb14cc37ea26c4f4451ce8","first_computed_at":"2026-05-18T02:39:00.768580Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:39:00.768580Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"508t2cgW64TD3OdeoRsSV+VzeGMgcQ+ssPr+lEILiIZftGHbZnumMCvrpKMg2mwos6OxK46TTykwntGlDwqwBg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:39:00.769220Z","signed_message":"canonical_sha256_bytes"},"source_id":"1407.7644","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c8b96897532442eacdf7495076254874fc15f4462ea35fb1a06b1b3270585589","sha256:14c55b12e3e65a0d513f659fcf4a9ac32e9c725157774c9756007f19562fd0e5"],"state_sha256":"ff3f148f9940df4f085ae9bc852afc995f1bd5361ca4e739789cd7e0288a5728"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VbAuZTWzsgwb1DhrcQzVcIWY1ChB24smQbg/21zTVkbdzPNFvTGaHigA79WRsbBKYfWUjIB4LjPS6Yum3aSdDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-04T09:54:33.655352Z","bundle_sha256":"ca063e43a05d130629df25a9934266280068213c700589e75a57f3d3218b5689"}}