{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:MQOFNC4AOWDJIRKVBBWZ6AZCKD","short_pith_number":"pith:MQOFNC4A","canonical_record":{"source":{"id":"2303.16507","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-29T07:34:20Z","cross_cats_sorted":[],"title_canon_sha256":"7f6b6483c2f6b6b9d5d3f33780f1b296838eaa0142c8ba0035ce4a174eb02bc5","abstract_canon_sha256":"ca6171c9c80bce6e61459c79df8214deacfa408dc759d8edac92522d0f8a7f67"},"schema_version":"1.0"},"canonical_sha256":"641c568b807586944555086d9f032250fe78359b500053f79e852b4b85dc96d3","source":{"kind":"arxiv","id":"2303.16507","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.16507","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"arxiv_version","alias_value":"2303.16507v1","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.16507","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"pith_short_12","alias_value":"MQOFNC4AOWDJ","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"pith_short_16","alias_value":"MQOFNC4AOWDJIRKV","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"pith_short_8","alias_value":"MQOFNC4A","created_at":"2026-07-05T05:56:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:MQOFNC4AOWDJIRKVBBWZ6AZCKD","target":"record","payload":{"canonical_record":{"source":{"id":"2303.16507","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-29T07:34:20Z","cross_cats_sorted":[],"title_canon_sha256":"7f6b6483c2f6b6b9d5d3f33780f1b296838eaa0142c8ba0035ce4a174eb02bc5","abstract_canon_sha256":"ca6171c9c80bce6e61459c79df8214deacfa408dc759d8edac92522d0f8a7f67"},"schema_version":"1.0"},"canonical_sha256":"641c568b807586944555086d9f032250fe78359b500053f79e852b4b85dc96d3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:56:07.716894Z","signature_b64":"4Wxp1/K53ZfkXWUikcb+35mUtGxAdScOvhGwMge3V6JR6KRIJWIsgSgVx0UK3/zOYFl0UlYKTcFOitRjObnyAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"641c568b807586944555086d9f032250fe78359b500053f79e852b4b85dc96d3","last_reissued_at":"2026-07-05T05:56:07.716358Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:56:07.716358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.16507","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":"2026-07-05T05:56:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XxXptO3xfVD3KSG+B2DW0VEmact10MBRbPgnCFjaF1+9tbiLxtEG6LtdaIFwDPzChcXOrQp7tf4ZedCg7rmMAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T09:43:48.111138Z"},"content_sha256":"a20913e3b0b5d56a23df65d07360958ba151aad5f3891d9a715549d5e176facb","schema_version":"1.0","event_id":"sha256:a20913e3b0b5d56a23df65d07360958ba151aad5f3891d9a715549d5e176facb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:MQOFNC4AOWDJIRKVBBWZ6AZCKD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ha Q. Nguyen, Hieu H. Pham, Khiem H. Le, Tuan V. Tran","submitted_at":"2023-03-29T07:34:20Z","abstract_excerpt":"The work discusses the use of machine learning algorithms for anomaly detection in medical image analysis and how the performance of these algorithms depends on the number of annotators and the quality of labels. To address the issue of subjectivity in labeling with a single annotator, we introduce a simple and effective approach that aggregates annotations from multiple annotators with varying levels of expertise. We then aim to improve the efficiency of predictive models in abnormal detection tasks by estimating hidden labels from multiple annotations and using a re-weighted loss function to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.16507","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/2303.16507/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":"2026-07-05T05:56:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5PTlrQki2NTt+O8Dzc48WJYNO/rfZ5wbttG1zPJfCLjZ3/zX03/VJVcl5Sh4n5MDXSR9bOgTjsxGzcec5YAQCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T09:43:48.112047Z"},"content_sha256":"b9564aad44a1bc9c050ab2e61f2056b41ac713abebc4699e708602b48ca54b5d","schema_version":"1.0","event_id":"sha256:b9564aad44a1bc9c050ab2e61f2056b41ac713abebc4699e708602b48ca54b5d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MQOFNC4AOWDJIRKVBBWZ6AZCKD/bundle.json","state_url":"https://pith.science/pith/MQOFNC4AOWDJIRKVBBWZ6AZCKD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MQOFNC4AOWDJIRKVBBWZ6AZCKD/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":"2026-08-04T09:43:48Z","links":{"resolver":"https://pith.science/pith/MQOFNC4AOWDJIRKVBBWZ6AZCKD","bundle":"https://pith.science/pith/MQOFNC4AOWDJIRKVBBWZ6AZCKD/bundle.json","state":"https://pith.science/pith/MQOFNC4AOWDJIRKVBBWZ6AZCKD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MQOFNC4AOWDJIRKVBBWZ6AZCKD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:MQOFNC4AOWDJIRKVBBWZ6AZCKD","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":"ca6171c9c80bce6e61459c79df8214deacfa408dc759d8edac92522d0f8a7f67","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-29T07:34:20Z","title_canon_sha256":"7f6b6483c2f6b6b9d5d3f33780f1b296838eaa0142c8ba0035ce4a174eb02bc5"},"schema_version":"1.0","source":{"id":"2303.16507","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.16507","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"arxiv_version","alias_value":"2303.16507v1","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.16507","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"pith_short_12","alias_value":"MQOFNC4AOWDJ","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"pith_short_16","alias_value":"MQOFNC4AOWDJIRKV","created_at":"2026-07-05T05:56:07Z"},{"alias_kind":"pith_short_8","alias_value":"MQOFNC4A","created_at":"2026-07-05T05:56:07Z"}],"graph_snapshots":[{"event_id":"sha256:b9564aad44a1bc9c050ab2e61f2056b41ac713abebc4699e708602b48ca54b5d","target":"graph","created_at":"2026-07-05T05:56:07Z","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/2303.16507/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The work discusses the use of machine learning algorithms for anomaly detection in medical image analysis and how the performance of these algorithms depends on the number of annotators and the quality of labels. To address the issue of subjectivity in labeling with a single annotator, we introduce a simple and effective approach that aggregates annotations from multiple annotators with varying levels of expertise. We then aim to improve the efficiency of predictive models in abnormal detection tasks by estimating hidden labels from multiple annotations and using a re-weighted loss function to","authors_text":"Ha Q. Nguyen, Hieu H. Pham, Khiem H. Le, Tuan V. Tran","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-29T07:34:20Z","title":"Improving Object Detection in Medical Image Analysis through Multiple Expert Annotators: An Empirical Investigation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.16507","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:a20913e3b0b5d56a23df65d07360958ba151aad5f3891d9a715549d5e176facb","target":"record","created_at":"2026-07-05T05:56:07Z","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":"ca6171c9c80bce6e61459c79df8214deacfa408dc759d8edac92522d0f8a7f67","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-03-29T07:34:20Z","title_canon_sha256":"7f6b6483c2f6b6b9d5d3f33780f1b296838eaa0142c8ba0035ce4a174eb02bc5"},"schema_version":"1.0","source":{"id":"2303.16507","kind":"arxiv","version":1}},"canonical_sha256":"641c568b807586944555086d9f032250fe78359b500053f79e852b4b85dc96d3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"641c568b807586944555086d9f032250fe78359b500053f79e852b4b85dc96d3","first_computed_at":"2026-07-05T05:56:07.716358Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:56:07.716358Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"4Wxp1/K53ZfkXWUikcb+35mUtGxAdScOvhGwMge3V6JR6KRIJWIsgSgVx0UK3/zOYFl0UlYKTcFOitRjObnyAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:56:07.716894Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.16507","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a20913e3b0b5d56a23df65d07360958ba151aad5f3891d9a715549d5e176facb","sha256:b9564aad44a1bc9c050ab2e61f2056b41ac713abebc4699e708602b48ca54b5d"],"state_sha256":"03b05f2403fbfd381d33a96d3e090672ee1fc035edb9c8345d0b2711eaadd1d5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AKSGTYQaZPahrVD4ywcsfCpqnKfh2ra0q9FlnXQcx/2CnlOX0J8uSWeZefCQMZGk5Y7Rt9Xy4dIb4AgeejnnBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T09:43:48.118700Z","bundle_sha256":"9324b55fa556875cd7ff27826275afcb04e6bdeb39aac04fa19f426d616bed62"}}