{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:24RRMZPROBGY3S2BRHZDQPI6W5","short_pith_number":"pith:24RRMZPR","canonical_record":{"source":{"id":"2309.08313","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2023-09-15T11:10:46Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5198740913c5fade44f5e310a559a09c84fc7e243c140284bda154edc1463cee","abstract_canon_sha256":"b03a3cb06aa6f518d4714bc235791e92cd14403b65158d85e37a531060708430"},"schema_version":"1.0"},"canonical_sha256":"d7231665f1704d8dcb4189f2383d1eb75ef41c5e417b0622f6059ece7fcfc007","source":{"kind":"arxiv","id":"2309.08313","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.08313","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"arxiv_version","alias_value":"2309.08313v2","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.08313","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"pith_short_12","alias_value":"24RRMZPROBGY","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"pith_short_16","alias_value":"24RRMZPROBGY3S2B","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"pith_short_8","alias_value":"24RRMZPR","created_at":"2026-07-05T08:13:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:24RRMZPROBGY3S2BRHZDQPI6W5","target":"record","payload":{"canonical_record":{"source":{"id":"2309.08313","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2023-09-15T11:10:46Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5198740913c5fade44f5e310a559a09c84fc7e243c140284bda154edc1463cee","abstract_canon_sha256":"b03a3cb06aa6f518d4714bc235791e92cd14403b65158d85e37a531060708430"},"schema_version":"1.0"},"canonical_sha256":"d7231665f1704d8dcb4189f2383d1eb75ef41c5e417b0622f6059ece7fcfc007","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:13:52.408963Z","signature_b64":"Q17sNJyCB/DTJ28FlhzLl68tDVezRAPurRZEMZvPqJyGSPtez+zbsL89cERPTDaWkAiOmDZsHn5/+iehE30NBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d7231665f1704d8dcb4189f2383d1eb75ef41c5e417b0622f6059ece7fcfc007","last_reissued_at":"2026-07-05T08:13:52.408569Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:13:52.408569Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.08313","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":"2026-07-05T08:13:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dRJ/9XzXNP72Ac5OuaGSVzyppwvsgFZczRDoVtv2Qc0RKXMb8AtwbgXzpCtf7ArB8y3y3PB3U+/axlH/y7kbBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T12:53:48.332240Z"},"content_sha256":"3e9757582da21325977e50a2986f29b282c2103d8059390f4fcdcebe6addf877","schema_version":"1.0","event_id":"sha256:3e9757582da21325977e50a2986f29b282c2103d8059390f4fcdcebe6addf877"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:24RRMZPROBGY3S2BRHZDQPI6W5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Conditional validity of heteroskedastic conformal regression","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Bernard De Baets, Nicolas Dewolf, Willem Waegeman","submitted_at":"2023-09-15T11:10:46Z","abstract_excerpt":"Conformal prediction, and split conformal prediction as a specific implementation, offer a distribution-free approach to estimating prediction intervals with statistical guarantees. Recent work has shown that split conformal prediction can produce state-of-the-art prediction intervals when focusing on marginal coverage, i.e. on a calibration dataset the method produces on average prediction intervals that contain the ground truth with a predefined coverage level. However, such intervals are often not adaptive, which can be problematic for regression problems with heteroskedastic noise. This pa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.08313","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/2309.08313/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":"2026-07-05T08:13:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6rXH/MLGYfnqsWNOjqc83ykzENI6zgQ6XRKc/BRIArpFogUmslShJn4ziU14uvBC53ggJ2ujNqBfGagf2V0lAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T12:53:48.332744Z"},"content_sha256":"aefbfbbb9bb2f7e27d4ad70c3b2073951040da066f3a966960ab36e08e1db871","schema_version":"1.0","event_id":"sha256:aefbfbbb9bb2f7e27d4ad70c3b2073951040da066f3a966960ab36e08e1db871"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/24RRMZPROBGY3S2BRHZDQPI6W5/bundle.json","state_url":"https://pith.science/pith/24RRMZPROBGY3S2BRHZDQPI6W5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/24RRMZPROBGY3S2BRHZDQPI6W5/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":"2026-08-08T12:53:48Z","links":{"resolver":"https://pith.science/pith/24RRMZPROBGY3S2BRHZDQPI6W5","bundle":"https://pith.science/pith/24RRMZPROBGY3S2BRHZDQPI6W5/bundle.json","state":"https://pith.science/pith/24RRMZPROBGY3S2BRHZDQPI6W5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/24RRMZPROBGY3S2BRHZDQPI6W5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:24RRMZPROBGY3S2BRHZDQPI6W5","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":"b03a3cb06aa6f518d4714bc235791e92cd14403b65158d85e37a531060708430","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2023-09-15T11:10:46Z","title_canon_sha256":"5198740913c5fade44f5e310a559a09c84fc7e243c140284bda154edc1463cee"},"schema_version":"1.0","source":{"id":"2309.08313","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.08313","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"arxiv_version","alias_value":"2309.08313v2","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.08313","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"pith_short_12","alias_value":"24RRMZPROBGY","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"pith_short_16","alias_value":"24RRMZPROBGY3S2B","created_at":"2026-07-05T08:13:52Z"},{"alias_kind":"pith_short_8","alias_value":"24RRMZPR","created_at":"2026-07-05T08:13:52Z"}],"graph_snapshots":[{"event_id":"sha256:aefbfbbb9bb2f7e27d4ad70c3b2073951040da066f3a966960ab36e08e1db871","target":"graph","created_at":"2026-07-05T08:13:52Z","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/2309.08313/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conformal prediction, and split conformal prediction as a specific implementation, offer a distribution-free approach to estimating prediction intervals with statistical guarantees. Recent work has shown that split conformal prediction can produce state-of-the-art prediction intervals when focusing on marginal coverage, i.e. on a calibration dataset the method produces on average prediction intervals that contain the ground truth with a predefined coverage level. However, such intervals are often not adaptive, which can be problematic for regression problems with heteroskedastic noise. This pa","authors_text":"Bernard De Baets, Nicolas Dewolf, Willem Waegeman","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2023-09-15T11:10:46Z","title":"Conditional validity of heteroskedastic conformal regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.08313","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":"sha256:3e9757582da21325977e50a2986f29b282c2103d8059390f4fcdcebe6addf877","target":"record","created_at":"2026-07-05T08:13:52Z","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":"b03a3cb06aa6f518d4714bc235791e92cd14403b65158d85e37a531060708430","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"stat.ML","submitted_at":"2023-09-15T11:10:46Z","title_canon_sha256":"5198740913c5fade44f5e310a559a09c84fc7e243c140284bda154edc1463cee"},"schema_version":"1.0","source":{"id":"2309.08313","kind":"arxiv","version":2}},"canonical_sha256":"d7231665f1704d8dcb4189f2383d1eb75ef41c5e417b0622f6059ece7fcfc007","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7231665f1704d8dcb4189f2383d1eb75ef41c5e417b0622f6059ece7fcfc007","first_computed_at":"2026-07-05T08:13:52.408569Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:13:52.408569Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Q17sNJyCB/DTJ28FlhzLl68tDVezRAPurRZEMZvPqJyGSPtez+zbsL89cERPTDaWkAiOmDZsHn5/+iehE30NBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:13:52.408963Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.08313","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e9757582da21325977e50a2986f29b282c2103d8059390f4fcdcebe6addf877","sha256:aefbfbbb9bb2f7e27d4ad70c3b2073951040da066f3a966960ab36e08e1db871"],"state_sha256":"5c3e873a9cb692c56b3e88956bb5fc7b7314376c5d87566683e1b6fbb5067dc4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AQ3jaHbGE2ScdLYhr+TsTBNyBGqi6YvGD6lcZN4CZy+jMhj9LoqNEFqNls9s5sjWMATrNMD5HCZLkJE4l5KgCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T12:53:48.337815Z","bundle_sha256":"e9c3adb301dfab35ba9b25c2fe5e7631fafe1e7fbf8c163aa970a806481b3b57"}}