{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:WLE5QFGWUZMSLTGCES5BM5KRSZ","short_pith_number":"pith:WLE5QFGW","canonical_record":{"source":{"id":"2302.03116","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-02-06T20:46:32Z","cross_cats_sorted":[],"title_canon_sha256":"0fd715860a5fa7258699fab428bcff16424d0053371c7746d14bdafc626650ec","abstract_canon_sha256":"64251c05d6f895091847b3192a1aa5f5d83e6b7f8c87f6b4a9fd63644e293f67"},"schema_version":"1.0"},"canonical_sha256":"b2c9d814d6a65925ccc224ba167551965719501be8c3fba5f6cb7fb3f21cc3f0","source":{"kind":"arxiv","id":"2302.03116","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.03116","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"arxiv_version","alias_value":"2302.03116v1","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.03116","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"pith_short_12","alias_value":"WLE5QFGWUZMS","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"pith_short_16","alias_value":"WLE5QFGWUZMSLTGC","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"pith_short_8","alias_value":"WLE5QFGW","created_at":"2026-07-05T05:39:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:WLE5QFGWUZMSLTGCES5BM5KRSZ","target":"record","payload":{"canonical_record":{"source":{"id":"2302.03116","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-02-06T20:46:32Z","cross_cats_sorted":[],"title_canon_sha256":"0fd715860a5fa7258699fab428bcff16424d0053371c7746d14bdafc626650ec","abstract_canon_sha256":"64251c05d6f895091847b3192a1aa5f5d83e6b7f8c87f6b4a9fd63644e293f67"},"schema_version":"1.0"},"canonical_sha256":"b2c9d814d6a65925ccc224ba167551965719501be8c3fba5f6cb7fb3f21cc3f0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:39:33.824422Z","signature_b64":"PsQCldoJObxe5Ikg9ymVZbb5G8Rikr49H2Y/68CYFw5Jl1miOEOhgcqZix3j0xYie15XpkmxcAARP+KOcACOCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b2c9d814d6a65925ccc224ba167551965719501be8c3fba5f6cb7fb3f21cc3f0","last_reissued_at":"2026-07-05T05:39:33.824021Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:39:33.824021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.03116","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":"2026-07-05T05:39:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JiAHh8H7vmP5AGLrfCijzBE0wluW0YDtJvKv49yjIynphqtY7y4nx3WJqDiUMo3dXUsRJOOAcdrp4MSqWENpBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:00:08.189177Z"},"content_sha256":"5518ba175a44642e3a61d1114215f15ebe51d9b37ddaf316eb85db07896abe67","schema_version":"1.0","event_id":"sha256:5518ba175a44642e3a61d1114215f15ebe51d9b37ddaf316eb85db07896abe67"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:WLE5QFGWUZMSLTGCES5BM5KRSZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Uncertainty-Aware Multiple-Instance Learning for Reliable Classification: Application to Optical Coherence Tomography","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"eess.IV","authors_text":"Bram van Ginneken, Carel B. Hoyng, Caroline C. W. Klaver, Clara I. S\\'anchez, Coen de Vente","submitted_at":"2023-02-06T20:46:32Z","abstract_excerpt":"Deep learning classification models for medical image analysis often perform well on data from scanners that were used during training. However, when these models are applied to data from different vendors, their performance tends to drop substantially. Artifacts that only occur within scans from specific scanners are major causes of this poor generalizability. We aimed to improve the reliability of deep learning classification models by proposing Uncertainty-Based Instance eXclusion (UBIX). This technique, based on multiple-instance learning, reduces the effect of corrupted instances on the b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.03116","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/2302.03116/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":"2026-07-05T05:39:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t4ymfG0CTXiBLlF9MMxeVEgTjLH7vdQSbnjllF+RYekgaF+9y6QvTKRJPZTd/pp9GbiUG558WuCPKXLKStlSDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T15:00:08.189836Z"},"content_sha256":"7c3d665d99f33bad0fb1ca02b2fb027d1a28bb8fcefe10af49fe2f7589a88882","schema_version":"1.0","event_id":"sha256:7c3d665d99f33bad0fb1ca02b2fb027d1a28bb8fcefe10af49fe2f7589a88882"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WLE5QFGWUZMSLTGCES5BM5KRSZ/bundle.json","state_url":"https://pith.science/pith/WLE5QFGWUZMSLTGCES5BM5KRSZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WLE5QFGWUZMSLTGCES5BM5KRSZ/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":"2026-07-05T15:00:08Z","links":{"resolver":"https://pith.science/pith/WLE5QFGWUZMSLTGCES5BM5KRSZ","bundle":"https://pith.science/pith/WLE5QFGWUZMSLTGCES5BM5KRSZ/bundle.json","state":"https://pith.science/pith/WLE5QFGWUZMSLTGCES5BM5KRSZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WLE5QFGWUZMSLTGCES5BM5KRSZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WLE5QFGWUZMSLTGCES5BM5KRSZ","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":"64251c05d6f895091847b3192a1aa5f5d83e6b7f8c87f6b4a9fd63644e293f67","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-02-06T20:46:32Z","title_canon_sha256":"0fd715860a5fa7258699fab428bcff16424d0053371c7746d14bdafc626650ec"},"schema_version":"1.0","source":{"id":"2302.03116","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.03116","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"arxiv_version","alias_value":"2302.03116v1","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.03116","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"pith_short_12","alias_value":"WLE5QFGWUZMS","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"pith_short_16","alias_value":"WLE5QFGWUZMSLTGC","created_at":"2026-07-05T05:39:33Z"},{"alias_kind":"pith_short_8","alias_value":"WLE5QFGW","created_at":"2026-07-05T05:39:33Z"}],"graph_snapshots":[{"event_id":"sha256:7c3d665d99f33bad0fb1ca02b2fb027d1a28bb8fcefe10af49fe2f7589a88882","target":"graph","created_at":"2026-07-05T05:39:33Z","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/2302.03116/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning classification models for medical image analysis often perform well on data from scanners that were used during training. However, when these models are applied to data from different vendors, their performance tends to drop substantially. Artifacts that only occur within scans from specific scanners are major causes of this poor generalizability. We aimed to improve the reliability of deep learning classification models by proposing Uncertainty-Based Instance eXclusion (UBIX). This technique, based on multiple-instance learning, reduces the effect of corrupted instances on the b","authors_text":"Bram van Ginneken, Carel B. Hoyng, Caroline C. W. Klaver, Clara I. S\\'anchez, Coen de Vente","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-02-06T20:46:32Z","title":"Uncertainty-Aware Multiple-Instance Learning for Reliable Classification: Application to Optical Coherence Tomography"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.03116","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":"sha256:5518ba175a44642e3a61d1114215f15ebe51d9b37ddaf316eb85db07896abe67","target":"record","created_at":"2026-07-05T05:39:33Z","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":"64251c05d6f895091847b3192a1aa5f5d83e6b7f8c87f6b4a9fd63644e293f67","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-02-06T20:46:32Z","title_canon_sha256":"0fd715860a5fa7258699fab428bcff16424d0053371c7746d14bdafc626650ec"},"schema_version":"1.0","source":{"id":"2302.03116","kind":"arxiv","version":1}},"canonical_sha256":"b2c9d814d6a65925ccc224ba167551965719501be8c3fba5f6cb7fb3f21cc3f0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b2c9d814d6a65925ccc224ba167551965719501be8c3fba5f6cb7fb3f21cc3f0","first_computed_at":"2026-07-05T05:39:33.824021Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:39:33.824021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PsQCldoJObxe5Ikg9ymVZbb5G8Rikr49H2Y/68CYFw5Jl1miOEOhgcqZix3j0xYie15XpkmxcAARP+KOcACOCg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:39:33.824422Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.03116","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5518ba175a44642e3a61d1114215f15ebe51d9b37ddaf316eb85db07896abe67","sha256:7c3d665d99f33bad0fb1ca02b2fb027d1a28bb8fcefe10af49fe2f7589a88882"],"state_sha256":"c1beedc096f5d9f2c1c43dafd3020eb8b309d99c11248424e89165c20a70b48e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UwN02bMRlih3VhknhnP+w++63cnVxd986AeJvOpBHAdms5vV0ZkLH34/d9PfL+KQhsETxmq38y/0iMkls6gjCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T15:00:08.193523Z","bundle_sha256":"291f48cabeb65f361682210851eefaa3380ebe588445aa6ea4b5febb345eed8b"}}