{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KYR2H4ER24AXEMLGFGZ43GBENP","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":"191d4f4b6fb24837ccde9a2a8c92256c309001134c4802575479b0e725fc8d99","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-05T14:03:16Z","title_canon_sha256":"6a3464917414a65a05794288b20bf6a0e2f707a6b1de31cafa1158b28d52b735"},"schema_version":"1.0","source":{"id":"2412.04166","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.04166","created_at":"2026-07-05T09:45:00Z"},{"alias_kind":"arxiv_version","alias_value":"2412.04166v1","created_at":"2026-07-05T09:45:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.04166","created_at":"2026-07-05T09:45:00Z"},{"alias_kind":"pith_short_12","alias_value":"KYR2H4ER24AX","created_at":"2026-07-05T09:45:00Z"},{"alias_kind":"pith_short_16","alias_value":"KYR2H4ER24AXEMLG","created_at":"2026-07-05T09:45:00Z"},{"alias_kind":"pith_short_8","alias_value":"KYR2H4ER","created_at":"2026-07-05T09:45:00Z"}],"graph_snapshots":[{"event_id":"sha256:3f67d4fe7b5968b53a282c23882d959a785272b40a50099b6a668342b84628fa","target":"graph","created_at":"2026-07-05T09:45:00Z","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/2412.04166/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Advanced classification algorithms are being increasingly used in safety-critical applications like health-care, engineering, etc. In such applications, miss-classifications made by ML algorithms can result in substantial financial or health-related losses. To better anticipate and prepare for such losses, the algorithm user seeks an estimate for the probability that the algorithm miss-classifies a sample. We refer to this task as the risk-assessment. For a variety of models and datasets, we numerically analyze the performance of different methods in solving the risk-assessment problem. We con","authors_text":"Disha Ghandwani, Neeraj Sarna, Yang Lin, Yuanyuan Li","cross_cats":["cs.NA","math.NA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-05T14:03:16Z","title":"An In-Depth Examination of Risk Assessment in Multi-Class Classification Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.04166","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:ca432ead4778c3ddf01fce058b693476f277343268a712f9a2a8ce8c181a26af","target":"record","created_at":"2026-07-05T09:45:00Z","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":"191d4f4b6fb24837ccde9a2a8c92256c309001134c4802575479b0e725fc8d99","cross_cats_sorted":["cs.NA","math.NA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-12-05T14:03:16Z","title_canon_sha256":"6a3464917414a65a05794288b20bf6a0e2f707a6b1de31cafa1158b28d52b735"},"schema_version":"1.0","source":{"id":"2412.04166","kind":"arxiv","version":1}},"canonical_sha256":"5623a3f091d70172316629b3cd98246be05d66605c26158bff6ef827512cc56e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5623a3f091d70172316629b3cd98246be05d66605c26158bff6ef827512cc56e","first_computed_at":"2026-07-05T09:45:00.294404Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:45:00.294404Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pl+UKn3I64xjGYOnkHj378nWSVWrNhyo3wrCqd2xN3DkYIaeEVLc7JInnTo0bBGeTD0YszmwCP35OIS61/drDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:45:00.294887Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.04166","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ca432ead4778c3ddf01fce058b693476f277343268a712f9a2a8ce8c181a26af","sha256:3f67d4fe7b5968b53a282c23882d959a785272b40a50099b6a668342b84628fa"],"state_sha256":"f3517d75ff948b0f8a1d59f6fade06a5b643d5864724e930d35da5dd34599e04"}