{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:7E2XKEHEISEACT7XHPUOYAVCQ2","short_pith_number":"pith:7E2XKEHE","canonical_record":{"source":{"id":"2405.02648","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-04T12:22:02Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"65a0ba950551b214422b86600ef22a96cac605a34abda1aea021f83ce1189d83","abstract_canon_sha256":"95481d90ccc66c5fcf12fbfc8175f38e66ebf777e3d233c0897673d52c5d8c78"},"schema_version":"1.0"},"canonical_sha256":"f9357510e44488014ff73be8ec02a286afec7ce5cf32ef06f99d65d84dbbd149","source":{"kind":"arxiv","id":"2405.02648","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.02648","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"arxiv_version","alias_value":"2405.02648v2","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.02648","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"pith_short_12","alias_value":"7E2XKEHEISEA","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"pith_short_16","alias_value":"7E2XKEHEISEACT7X","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"pith_short_8","alias_value":"7E2XKEHE","created_at":"2026-07-05T08:21:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:7E2XKEHEISEACT7XHPUOYAVCQ2","target":"record","payload":{"canonical_record":{"source":{"id":"2405.02648","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-04T12:22:02Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"65a0ba950551b214422b86600ef22a96cac605a34abda1aea021f83ce1189d83","abstract_canon_sha256":"95481d90ccc66c5fcf12fbfc8175f38e66ebf777e3d233c0897673d52c5d8c78"},"schema_version":"1.0"},"canonical_sha256":"f9357510e44488014ff73be8ec02a286afec7ce5cf32ef06f99d65d84dbbd149","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:21:15.880493Z","signature_b64":"72lsF6k0R2GZZwXZ43V8sxZij0T9YQQdaKMxFXe08C+ruRJdQcQUK2eCR7spP/C5YT13KkcRnLwt4KdRKwDDBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f9357510e44488014ff73be8ec02a286afec7ce5cf32ef06f99d65d84dbbd149","last_reissued_at":"2026-07-05T08:21:15.880062Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:21:15.880062Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.02648","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":"2026-07-05T08:21:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oHk/orEALIBVrvfldFNKqpeVZMAQu3sKDXJcztAecnB4to19Y/ch4Qr8eD80h3c2eJR8gphhpvvkrgGRs/tSAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:03:09.322067Z"},"content_sha256":"947c78784701dcb39ac15e15962338ef45f5061708bb49d186155373f9d10b3c","schema_version":"1.0","event_id":"sha256:947c78784701dcb39ac15e15962338ef45f5061708bb49d186155373f9d10b3c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:7E2XKEHEISEACT7XHPUOYAVCQ2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Conformal Prediction Score that is Robust to Label Noise","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Coby Penso, Jacob Goldberger","submitted_at":"2024-05-04T12:22:02Z","abstract_excerpt":"Conformal Prediction (CP) quantifies network uncertainty by building a small prediction set with a pre-defined probability that the correct class is within this set. In this study we tackle the problem of CP calibration based on a validation set with noisy labels. We introduce a conformal score that is robust to label noise. The noise-free conformal score is estimated using the noisy labeled data and the noise level. In the test phase the noise-free score is used to form the prediction set. We applied the proposed algorithm to several standard medical imaging classification datasets. We show t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.02648","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2405.02648/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":"2026-07-05T08:21:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AwDPXW7ShuE5YTPcgo0sDtqJS17orQTDn5d1pDD1na0hFaFAHoekFGgPThAiIoBOb4rtOMriQyBojO/bSWsuBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T02:03:09.322574Z"},"content_sha256":"bfbfc8b3d892fb8e9f9d96b94f5fef7bd5b8b5af9148df06fea2925d36725a6a","schema_version":"1.0","event_id":"sha256:bfbfc8b3d892fb8e9f9d96b94f5fef7bd5b8b5af9148df06fea2925d36725a6a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7E2XKEHEISEACT7XHPUOYAVCQ2/bundle.json","state_url":"https://pith.science/pith/7E2XKEHEISEACT7XHPUOYAVCQ2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7E2XKEHEISEACT7XHPUOYAVCQ2/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":"2026-08-05T02:03:09Z","links":{"resolver":"https://pith.science/pith/7E2XKEHEISEACT7XHPUOYAVCQ2","bundle":"https://pith.science/pith/7E2XKEHEISEACT7XHPUOYAVCQ2/bundle.json","state":"https://pith.science/pith/7E2XKEHEISEACT7XHPUOYAVCQ2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7E2XKEHEISEACT7XHPUOYAVCQ2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:7E2XKEHEISEACT7XHPUOYAVCQ2","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":"95481d90ccc66c5fcf12fbfc8175f38e66ebf777e3d233c0897673d52c5d8c78","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-04T12:22:02Z","title_canon_sha256":"65a0ba950551b214422b86600ef22a96cac605a34abda1aea021f83ce1189d83"},"schema_version":"1.0","source":{"id":"2405.02648","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.02648","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"arxiv_version","alias_value":"2405.02648v2","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.02648","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"pith_short_12","alias_value":"7E2XKEHEISEA","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"pith_short_16","alias_value":"7E2XKEHEISEACT7X","created_at":"2026-07-05T08:21:15Z"},{"alias_kind":"pith_short_8","alias_value":"7E2XKEHE","created_at":"2026-07-05T08:21:15Z"}],"graph_snapshots":[{"event_id":"sha256:bfbfc8b3d892fb8e9f9d96b94f5fef7bd5b8b5af9148df06fea2925d36725a6a","target":"graph","created_at":"2026-07-05T08:21:15Z","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/2405.02648/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conformal Prediction (CP) quantifies network uncertainty by building a small prediction set with a pre-defined probability that the correct class is within this set. In this study we tackle the problem of CP calibration based on a validation set with noisy labels. We introduce a conformal score that is robust to label noise. The noise-free conformal score is estimated using the noisy labeled data and the noise level. In the test phase the noise-free score is used to form the prediction set. We applied the proposed algorithm to several standard medical imaging classification datasets. We show t","authors_text":"Coby Penso, Jacob Goldberger","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-04T12:22:02Z","title":"A Conformal Prediction Score that is Robust to Label Noise"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.02648","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":"sha256:947c78784701dcb39ac15e15962338ef45f5061708bb49d186155373f9d10b3c","target":"record","created_at":"2026-07-05T08:21:15Z","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":"95481d90ccc66c5fcf12fbfc8175f38e66ebf777e3d233c0897673d52c5d8c78","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-04T12:22:02Z","title_canon_sha256":"65a0ba950551b214422b86600ef22a96cac605a34abda1aea021f83ce1189d83"},"schema_version":"1.0","source":{"id":"2405.02648","kind":"arxiv","version":2}},"canonical_sha256":"f9357510e44488014ff73be8ec02a286afec7ce5cf32ef06f99d65d84dbbd149","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f9357510e44488014ff73be8ec02a286afec7ce5cf32ef06f99d65d84dbbd149","first_computed_at":"2026-07-05T08:21:15.880062Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:21:15.880062Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"72lsF6k0R2GZZwXZ43V8sxZij0T9YQQdaKMxFXe08C+ruRJdQcQUK2eCR7spP/C5YT13KkcRnLwt4KdRKwDDBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:21:15.880493Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.02648","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:947c78784701dcb39ac15e15962338ef45f5061708bb49d186155373f9d10b3c","sha256:bfbfc8b3d892fb8e9f9d96b94f5fef7bd5b8b5af9148df06fea2925d36725a6a"],"state_sha256":"7520e6b90cce112742968ae07b03155b11ade0e753d3729007860f82ce3fd699"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VvZlnEvzR9joa6Ygwl4FPq1F+7f+NKFVxSsKnZ60BMNSrO8TITt2zbDcbdPwWJr1vhvLgxYwGCKgAXdXvy81Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T02:03:09.328230Z","bundle_sha256":"da2945335cc7814c0059c884a976fb5245deeb76daffc38f8423c3aac23f3705"}}