{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:G7KGYBYENOMXXYQT5DSN3DAT2M","short_pith_number":"pith:G7KGYBYE","canonical_record":{"source":{"id":"2507.06061","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-07-08T15:06:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c4f95e3f679eed834c49d4107e0d7f6523d15d3b4fabb270030313c1ed062b80","abstract_canon_sha256":"9d09d0a3d0c54340c118d1a9de189643e88ea2b1988c8d128856bef687e72927"},"schema_version":"1.0"},"canonical_sha256":"37d46c07046b997be213e8e4dd8c13d322f62fc979ce6b4d360714860050cd6b","source":{"kind":"arxiv","id":"2507.06061","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.06061","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"arxiv_version","alias_value":"2507.06061v1","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.06061","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"pith_short_12","alias_value":"G7KGYBYENOMX","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"pith_short_16","alias_value":"G7KGYBYENOMXXYQT","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"pith_short_8","alias_value":"G7KGYBYE","created_at":"2026-07-05T11:33:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:G7KGYBYENOMXXYQT5DSN3DAT2M","target":"record","payload":{"canonical_record":{"source":{"id":"2507.06061","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-07-08T15:06:02Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c4f95e3f679eed834c49d4107e0d7f6523d15d3b4fabb270030313c1ed062b80","abstract_canon_sha256":"9d09d0a3d0c54340c118d1a9de189643e88ea2b1988c8d128856bef687e72927"},"schema_version":"1.0"},"canonical_sha256":"37d46c07046b997be213e8e4dd8c13d322f62fc979ce6b4d360714860050cd6b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:33:40.894040Z","signature_b64":"nSsk38rUCAoB7gzvE0QmnNB3wSWmgv1frY1fieU4cZnKKrKHo3R6lUDzFSqdXgkAb/YeHA5Va+bS/aHLRZB9CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"37d46c07046b997be213e8e4dd8c13d322f62fc979ce6b4d360714860050cd6b","last_reissued_at":"2026-07-05T11:33:40.893640Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:33:40.893640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.06061","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":"2026-07-05T11:33:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V533fVY/fWFo7bv5cMCwA4xQE4zv5/fb0g6LFovdKRKsx5LbeonM8Xs+mc+sRlXJvd/Uy1XF/LIWCcFqxO71CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:11:40.064525Z"},"content_sha256":"b6e274e72a0c952a2b786203000d71ab7a75f7d7d1f8d773b2c09d39df575aa4","schema_version":"1.0","event_id":"sha256:b6e274e72a0c952a2b786203000d71ab7a75f7d7d1f8d773b2c09d39df575aa4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:G7KGYBYENOMXXYQT5DSN3DAT2M","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Estimating prevalence with precision and accuracy","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Aime Bienfait Igiraneza, Christophe Fraser, Robert Hinch","submitted_at":"2025-07-08T15:06:02Z","abstract_excerpt":"Unlike classification, whose goal is to estimate the class of each data point in a dataset, prevalence estimation or quantification is a task that aims to estimate the distribution of classes in a dataset. The two main tasks in prevalence estimation are to adjust for bias, due to the prevalence in the training dataset, and to quantify the uncertainty in the estimate. The standard methods used to quantify uncertainty in prevalence estimates are bootstrapping and Bayesian quantification methods. It is not clear which approach is ideal in terms of precision (i.e. the width of confidence intervals"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.06061","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.06061/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":"2026-07-05T11:33:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Lebwn3lOG71iSOz+eyQYX2BOhmx0mlGMSSg+msUqD3s4PwOx6dwvQCwDiJxQI0atoHSj+6dy6s7/G9URTkAJBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:11:40.065066Z"},"content_sha256":"e30107e399a49d4938a401361eb83974d38c13602f16caab4950016095a7c1fc","schema_version":"1.0","event_id":"sha256:e30107e399a49d4938a401361eb83974d38c13602f16caab4950016095a7c1fc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G7KGYBYENOMXXYQT5DSN3DAT2M/bundle.json","state_url":"https://pith.science/pith/G7KGYBYENOMXXYQT5DSN3DAT2M/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G7KGYBYENOMXXYQT5DSN3DAT2M/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":"2026-08-09T16:11:40Z","links":{"resolver":"https://pith.science/pith/G7KGYBYENOMXXYQT5DSN3DAT2M","bundle":"https://pith.science/pith/G7KGYBYENOMXXYQT5DSN3DAT2M/bundle.json","state":"https://pith.science/pith/G7KGYBYENOMXXYQT5DSN3DAT2M/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G7KGYBYENOMXXYQT5DSN3DAT2M/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:G7KGYBYENOMXXYQT5DSN3DAT2M","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":"9d09d0a3d0c54340c118d1a9de189643e88ea2b1988c8d128856bef687e72927","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-07-08T15:06:02Z","title_canon_sha256":"c4f95e3f679eed834c49d4107e0d7f6523d15d3b4fabb270030313c1ed062b80"},"schema_version":"1.0","source":{"id":"2507.06061","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.06061","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"arxiv_version","alias_value":"2507.06061v1","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.06061","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"pith_short_12","alias_value":"G7KGYBYENOMX","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"pith_short_16","alias_value":"G7KGYBYENOMXXYQT","created_at":"2026-07-05T11:33:40Z"},{"alias_kind":"pith_short_8","alias_value":"G7KGYBYE","created_at":"2026-07-05T11:33:40Z"}],"graph_snapshots":[{"event_id":"sha256:e30107e399a49d4938a401361eb83974d38c13602f16caab4950016095a7c1fc","target":"graph","created_at":"2026-07-05T11:33:40Z","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/2507.06061/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Unlike classification, whose goal is to estimate the class of each data point in a dataset, prevalence estimation or quantification is a task that aims to estimate the distribution of classes in a dataset. The two main tasks in prevalence estimation are to adjust for bias, due to the prevalence in the training dataset, and to quantify the uncertainty in the estimate. The standard methods used to quantify uncertainty in prevalence estimates are bootstrapping and Bayesian quantification methods. It is not clear which approach is ideal in terms of precision (i.e. the width of confidence intervals","authors_text":"Aime Bienfait Igiraneza, Christophe Fraser, Robert Hinch","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-07-08T15:06:02Z","title":"Estimating prevalence with precision and accuracy"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.06061","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:b6e274e72a0c952a2b786203000d71ab7a75f7d7d1f8d773b2c09d39df575aa4","target":"record","created_at":"2026-07-05T11:33:40Z","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":"9d09d0a3d0c54340c118d1a9de189643e88ea2b1988c8d128856bef687e72927","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2025-07-08T15:06:02Z","title_canon_sha256":"c4f95e3f679eed834c49d4107e0d7f6523d15d3b4fabb270030313c1ed062b80"},"schema_version":"1.0","source":{"id":"2507.06061","kind":"arxiv","version":1}},"canonical_sha256":"37d46c07046b997be213e8e4dd8c13d322f62fc979ce6b4d360714860050cd6b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"37d46c07046b997be213e8e4dd8c13d322f62fc979ce6b4d360714860050cd6b","first_computed_at":"2026-07-05T11:33:40.893640Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:33:40.893640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nSsk38rUCAoB7gzvE0QmnNB3wSWmgv1frY1fieU4cZnKKrKHo3R6lUDzFSqdXgkAb/YeHA5Va+bS/aHLRZB9CA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:33:40.894040Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.06061","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b6e274e72a0c952a2b786203000d71ab7a75f7d7d1f8d773b2c09d39df575aa4","sha256:e30107e399a49d4938a401361eb83974d38c13602f16caab4950016095a7c1fc"],"state_sha256":"9cbff1a76aa5ba9a7c3a76ff3323b20bc9d5b274512f58867d7ed4bc9cd9616c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YZo7aFhPZUeD0hVYKpVFO+VsHFX7Yok4+7Frslfm+kA1PpluyCHuWyDRODAVYbju4ai4JkF/1RW/ZYqVFjsRBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T16:11:40.070487Z","bundle_sha256":"f67f1ce9f6bfd041358eb2329c4d227351e20eee1c300f44a82172c801973e7c"}}