{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:7ZNYRLCTWH3JXEMBRNGAQ5KGLY","short_pith_number":"pith:7ZNYRLCT","canonical_record":{"source":{"id":"2302.07294","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-14T19:21:44Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"00fac5fc40f82f210be07bffab1ed62715e0925212eb6b27d865fe70c78a49a6","abstract_canon_sha256":"764fac6d06a6628372ef9ef86bcad0904241389fb709dabe4a80a4b27055a828"},"schema_version":"1.0"},"canonical_sha256":"fe5b88ac53b1f69b91818b4c0875465e1a9ce4e63d1f2ff8140b262d937b6b21","source":{"kind":"arxiv","id":"2302.07294","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.07294","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"arxiv_version","alias_value":"2302.07294v3","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.07294","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"pith_short_12","alias_value":"7ZNYRLCTWH3J","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"pith_short_16","alias_value":"7ZNYRLCTWH3JXEMB","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"pith_short_8","alias_value":"7ZNYRLCT","created_at":"2026-07-05T07:04:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:7ZNYRLCTWH3JXEMBRNGAQ5KGLY","target":"record","payload":{"canonical_record":{"source":{"id":"2302.07294","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-14T19:21:44Z","cross_cats_sorted":["stat.ME"],"title_canon_sha256":"00fac5fc40f82f210be07bffab1ed62715e0925212eb6b27d865fe70c78a49a6","abstract_canon_sha256":"764fac6d06a6628372ef9ef86bcad0904241389fb709dabe4a80a4b27055a828"},"schema_version":"1.0"},"canonical_sha256":"fe5b88ac53b1f69b91818b4c0875465e1a9ce4e63d1f2ff8140b262d937b6b21","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:04:12.953497Z","signature_b64":"CfKYIt0P5fMNp+WsvoYsgNQe70oBG8Fb9x4ZGEabS54fVptnpv/AzorUVDLdFrm5TUFdLyyRbqR3r2oy9tPLDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe5b88ac53b1f69b91818b4c0875465e1a9ce4e63d1f2ff8140b262d937b6b21","last_reissued_at":"2026-07-05T07:04:12.953098Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:04:12.953098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.07294","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:04:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WhsOoUNYxYwO0jAvWmHNKz/xKGONx7RPMGNkszHXS/jXnutF/siNnP8DtFlZBc6tgqtNY6inpf/Oek1LiXgPCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T23:15:20.060443Z"},"content_sha256":"25a4694ffc545583768a85e498baff466a2141ed14351867620d121a4cfa5071","schema_version":"1.0","event_id":"sha256:25a4694ffc545583768a85e498baff466a2141ed14351867620d121a4cfa5071"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:7ZNYRLCTWH3JXEMBRNGAQ5KGLY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Derandomized Novelty Detection with FDR Control via Conformal E-values","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ME"],"primary_cat":"cs.LG","authors_text":"Amir Epstein, Matteo Sesia, Meshi Bashari, Yaniv Romano","submitted_at":"2023-02-14T19:21:44Z","abstract_excerpt":"Conformal inference provides a general distribution-free method to rigorously calibrate the output of any machine learning algorithm for novelty detection. While this approach has many strengths, it has the limitation of being randomized, in the sense that it may lead to different results when analyzing twice the same data, and this can hinder the interpretation of any findings. We propose to make conformal inferences more stable by leveraging suitable conformal e-values instead of p-values to quantify statistical significance. This solution allows the evidence gathered from multiple analyses "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.07294","kind":"arxiv","version":3},"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/2302.07294/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":"2026-07-05T07:04:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E+tHC2rwLgwRcFLoNbC70eBeI1cCpf2/jBD6LD9gzekYHZ/jPZzwMYUH7SavLW9svnW4zmKKAuS1/DqOTfi4Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T23:15:20.061036Z"},"content_sha256":"54ba5f61d6a9e3f28ba54a33f5db7a42268c4bd3e458aab4d49ccf1c2ec89f97","schema_version":"1.0","event_id":"sha256:54ba5f61d6a9e3f28ba54a33f5db7a42268c4bd3e458aab4d49ccf1c2ec89f97"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7ZNYRLCTWH3JXEMBRNGAQ5KGLY/bundle.json","state_url":"https://pith.science/pith/7ZNYRLCTWH3JXEMBRNGAQ5KGLY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7ZNYRLCTWH3JXEMBRNGAQ5KGLY/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":"2026-08-14T23:15:20Z","links":{"resolver":"https://pith.science/pith/7ZNYRLCTWH3JXEMBRNGAQ5KGLY","bundle":"https://pith.science/pith/7ZNYRLCTWH3JXEMBRNGAQ5KGLY/bundle.json","state":"https://pith.science/pith/7ZNYRLCTWH3JXEMBRNGAQ5KGLY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7ZNYRLCTWH3JXEMBRNGAQ5KGLY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:7ZNYRLCTWH3JXEMBRNGAQ5KGLY","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":"764fac6d06a6628372ef9ef86bcad0904241389fb709dabe4a80a4b27055a828","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-14T19:21:44Z","title_canon_sha256":"00fac5fc40f82f210be07bffab1ed62715e0925212eb6b27d865fe70c78a49a6"},"schema_version":"1.0","source":{"id":"2302.07294","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.07294","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"arxiv_version","alias_value":"2302.07294v3","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.07294","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"pith_short_12","alias_value":"7ZNYRLCTWH3J","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"pith_short_16","alias_value":"7ZNYRLCTWH3JXEMB","created_at":"2026-07-05T07:04:12Z"},{"alias_kind":"pith_short_8","alias_value":"7ZNYRLCT","created_at":"2026-07-05T07:04:12Z"}],"graph_snapshots":[{"event_id":"sha256:54ba5f61d6a9e3f28ba54a33f5db7a42268c4bd3e458aab4d49ccf1c2ec89f97","target":"graph","created_at":"2026-07-05T07:04:12Z","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/2302.07294/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conformal inference provides a general distribution-free method to rigorously calibrate the output of any machine learning algorithm for novelty detection. While this approach has many strengths, it has the limitation of being randomized, in the sense that it may lead to different results when analyzing twice the same data, and this can hinder the interpretation of any findings. We propose to make conformal inferences more stable by leveraging suitable conformal e-values instead of p-values to quantify statistical significance. This solution allows the evidence gathered from multiple analyses ","authors_text":"Amir Epstein, Matteo Sesia, Meshi Bashari, Yaniv Romano","cross_cats":["stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-14T19:21:44Z","title":"Derandomized Novelty Detection with FDR Control via Conformal E-values"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.07294","kind":"arxiv","version":3},"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":"sha256:25a4694ffc545583768a85e498baff466a2141ed14351867620d121a4cfa5071","target":"record","created_at":"2026-07-05T07:04:12Z","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":"764fac6d06a6628372ef9ef86bcad0904241389fb709dabe4a80a4b27055a828","cross_cats_sorted":["stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-14T19:21:44Z","title_canon_sha256":"00fac5fc40f82f210be07bffab1ed62715e0925212eb6b27d865fe70c78a49a6"},"schema_version":"1.0","source":{"id":"2302.07294","kind":"arxiv","version":3}},"canonical_sha256":"fe5b88ac53b1f69b91818b4c0875465e1a9ce4e63d1f2ff8140b262d937b6b21","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe5b88ac53b1f69b91818b4c0875465e1a9ce4e63d1f2ff8140b262d937b6b21","first_computed_at":"2026-07-05T07:04:12.953098Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:04:12.953098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CfKYIt0P5fMNp+WsvoYsgNQe70oBG8Fb9x4ZGEabS54fVptnpv/AzorUVDLdFrm5TUFdLyyRbqR3r2oy9tPLDg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:04:12.953497Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.07294","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:25a4694ffc545583768a85e498baff466a2141ed14351867620d121a4cfa5071","sha256:54ba5f61d6a9e3f28ba54a33f5db7a42268c4bd3e458aab4d49ccf1c2ec89f97"],"state_sha256":"707139b56bd2aee348c0cb1443b5bca515ef38fc2bb8f1d8abf1e96ca9e2de4e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yp6//wWz9d8b93BqgMsr2Fx0ccbOgCoih70mnrUR9Q3RhCsn9AEIBpD6dfoRRlG4LraFgUXqQScW+KYvqU0QAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T23:15:20.066309Z","bundle_sha256":"9ad63f98e99e8f0978aa4652cad811d77f34e283c89031f956b299fec1894f73"}}