{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:L7M4V4XEA2TNTA6UL3J7MJ5EES","short_pith_number":"pith:L7M4V4XE","canonical_record":{"source":{"id":"2203.01937","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-03T08:04:59Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"c6aa4d03ece494733ad89a99d06bb02d627c0e1f68cabaa21630b13b9c5cde1d","abstract_canon_sha256":"1b9cc36795081b79cb397ad918b4d2ae5324a6702c08e4c4553e2e27ece4b51d"},"schema_version":"1.0"},"canonical_sha256":"5fd9caf2e406a6d983d45ed3f627a424b105ccd697508698d6e2cd38574e2957","source":{"kind":"arxiv","id":"2203.01937","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.01937","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"arxiv_version","alias_value":"2203.01937v5","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01937","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"pith_short_12","alias_value":"L7M4V4XEA2TN","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"pith_short_16","alias_value":"L7M4V4XEA2TNTA6U","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"pith_short_8","alias_value":"L7M4V4XE","created_at":"2026-07-05T06:39:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:L7M4V4XEA2TNTA6UL3J7MJ5EES","target":"record","payload":{"canonical_record":{"source":{"id":"2203.01937","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-03T08:04:59Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"c6aa4d03ece494733ad89a99d06bb02d627c0e1f68cabaa21630b13b9c5cde1d","abstract_canon_sha256":"1b9cc36795081b79cb397ad918b4d2ae5324a6702c08e4c4553e2e27ece4b51d"},"schema_version":"1.0"},"canonical_sha256":"5fd9caf2e406a6d983d45ed3f627a424b105ccd697508698d6e2cd38574e2957","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:39:29.179069Z","signature_b64":"urlYRILIfQtlaHHJALUNlfrFjzGJa9q6sZvzbKyUBGzB7fbe3Dj10rigd6wBUGPSi77iUkxikCqp5S6rkioYDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5fd9caf2e406a6d983d45ed3f627a424b105ccd697508698d6e2cd38574e2957","last_reissued_at":"2026-07-05T06:39:29.178545Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:39:29.178545Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.01937","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:39:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j0dZxFCaJIVOi3BvWF86nzwZlt9yMRB9ByZ58pj25bzJ2KDX6bUnBMNEDguLSMqmTt3qc86OzXZ5Thz1PfXfAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:43:25.557686Z"},"content_sha256":"5b19f793f8ea14e2725dda2ad0e4b21f8870dbedd28e0634c6381a89d9993c37","schema_version":"1.0","event_id":"sha256:5b19f793f8ea14e2725dda2ad0e4b21f8870dbedd28e0634c6381a89d9993c37"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:L7M4V4XEA2TNTA6UL3J7MJ5EES","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Chong Wang, Fengbei Liu, Gustavo Carneiro, Hu Wang, Yuanhong Chen, Yu Tian, Yuyuan Liu","submitted_at":"2022-03-03T08:04:59Z","abstract_excerpt":"Deep learning methods have shown outstanding classification accuracy in medical imaging problems, which is largely attributed to the availability of large-scale datasets manually annotated with clean labels. However, given the high cost of such manual annotation, new medical imaging classification problems may need to rely on machine-generated noisy labels extracted from radiology reports. Indeed, many Chest X-ray (CXR) classifiers have already been modelled from datasets with noisy labels, but their training procedure is in general not robust to noisy-label samples, leading to sub-optimal mod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01937","kind":"arxiv","version":5},"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/2203.01937/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":"2026-07-05T06:39:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PSM3RmBlTHoYiW+0bFCEsK1vqtob3Y10NkmhYGsdwJVcj7gfo7vuNhnWzi2fZ81YPMg9hEhfoBXLlrFbBg1/Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:43:25.558330Z"},"content_sha256":"51694e854c68b7fbcfe06a2b3c7a5dccbfcec551c6f57dc22147361e538aabce","schema_version":"1.0","event_id":"sha256:51694e854c68b7fbcfe06a2b3c7a5dccbfcec551c6f57dc22147361e538aabce"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L7M4V4XEA2TNTA6UL3J7MJ5EES/bundle.json","state_url":"https://pith.science/pith/L7M4V4XEA2TNTA6UL3J7MJ5EES/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L7M4V4XEA2TNTA6UL3J7MJ5EES/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":"2026-08-10T12:43:25Z","links":{"resolver":"https://pith.science/pith/L7M4V4XEA2TNTA6UL3J7MJ5EES","bundle":"https://pith.science/pith/L7M4V4XEA2TNTA6UL3J7MJ5EES/bundle.json","state":"https://pith.science/pith/L7M4V4XEA2TNTA6UL3J7MJ5EES/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L7M4V4XEA2TNTA6UL3J7MJ5EES/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:L7M4V4XEA2TNTA6UL3J7MJ5EES","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":"1b9cc36795081b79cb397ad918b4d2ae5324a6702c08e4c4553e2e27ece4b51d","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-03T08:04:59Z","title_canon_sha256":"c6aa4d03ece494733ad89a99d06bb02d627c0e1f68cabaa21630b13b9c5cde1d"},"schema_version":"1.0","source":{"id":"2203.01937","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.01937","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"arxiv_version","alias_value":"2203.01937v5","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01937","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"pith_short_12","alias_value":"L7M4V4XEA2TN","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"pith_short_16","alias_value":"L7M4V4XEA2TNTA6U","created_at":"2026-07-05T06:39:29Z"},{"alias_kind":"pith_short_8","alias_value":"L7M4V4XE","created_at":"2026-07-05T06:39:29Z"}],"graph_snapshots":[{"event_id":"sha256:51694e854c68b7fbcfe06a2b3c7a5dccbfcec551c6f57dc22147361e538aabce","target":"graph","created_at":"2026-07-05T06:39:29Z","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/2203.01937/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning methods have shown outstanding classification accuracy in medical imaging problems, which is largely attributed to the availability of large-scale datasets manually annotated with clean labels. However, given the high cost of such manual annotation, new medical imaging classification problems may need to rely on machine-generated noisy labels extracted from radiology reports. Indeed, many Chest X-ray (CXR) classifiers have already been modelled from datasets with noisy labels, but their training procedure is in general not robust to noisy-label samples, leading to sub-optimal mod","authors_text":"Chong Wang, Fengbei Liu, Gustavo Carneiro, Hu Wang, Yuanhong Chen, Yu Tian, Yuyuan Liu","cross_cats":["cs.AI","cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-03T08:04:59Z","title":"BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01937","kind":"arxiv","version":5},"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":"sha256:5b19f793f8ea14e2725dda2ad0e4b21f8870dbedd28e0634c6381a89d9993c37","target":"record","created_at":"2026-07-05T06:39:29Z","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":"1b9cc36795081b79cb397ad918b4d2ae5324a6702c08e4c4553e2e27ece4b51d","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-03T08:04:59Z","title_canon_sha256":"c6aa4d03ece494733ad89a99d06bb02d627c0e1f68cabaa21630b13b9c5cde1d"},"schema_version":"1.0","source":{"id":"2203.01937","kind":"arxiv","version":5}},"canonical_sha256":"5fd9caf2e406a6d983d45ed3f627a424b105ccd697508698d6e2cd38574e2957","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5fd9caf2e406a6d983d45ed3f627a424b105ccd697508698d6e2cd38574e2957","first_computed_at":"2026-07-05T06:39:29.178545Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:39:29.178545Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"urlYRILIfQtlaHHJALUNlfrFjzGJa9q6sZvzbKyUBGzB7fbe3Dj10rigd6wBUGPSi77iUkxikCqp5S6rkioYDw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:39:29.179069Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.01937","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5b19f793f8ea14e2725dda2ad0e4b21f8870dbedd28e0634c6381a89d9993c37","sha256:51694e854c68b7fbcfe06a2b3c7a5dccbfcec551c6f57dc22147361e538aabce"],"state_sha256":"aaeeec2a028c2295185bfbfcb917f136374412c12eb877da9e3d3374d4cde929"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xJiT7eN604Nb/rfGWo7qM4b+nOAGdkowulcW4NTlO7nXyiOMIYgffrg9+hWA+sQZXILs3KTtkMYkqKtjxCiJDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T12:43:25.563374Z","bundle_sha256":"270bcfb699905c9065a5c815c6594031d8227bf6dc2a541a27f0a2fe225ad585"}}