{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XDBCTCDN24C3IIG3NPQGJHLKRK","short_pith_number":"pith:XDBCTCDN","schema_version":"1.0","canonical_sha256":"b8c229886dd705b420db6be0649d6a8a8af07a133fc860cdd1d9e16a162d3371","source":{"kind":"arxiv","id":"2606.02676","version":1},"attestation_state":"computed","paper":{"title":"Diagnostic Tools for Extreme Value Regression Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Ed Mackay, Jordan Richards, Philip Jonathan","submitted_at":"2026-06-01T13:45:16Z","abstract_excerpt":"Visual and quantitative goodness-of-fit diagnostics are an important tool in the practitioner's toolbox. The need for convincing and reliable diagnostics is particularly clear when fitting extreme value regression models, which are used for extrapolation far beyond the observable range of the response variable, and often evaluated at unobserved covariate values. Despite this, few diagnostics have been developed for extreme value regression models, and those available often suffer in terms of interpretability or scalability on low-dimensional or non-Euclidean covariate domains, often encountere"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.02676","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2026-06-01T13:45:16Z","cross_cats_sorted":[],"title_canon_sha256":"815eba70b2e872c4e074fe16abd0c7d66cb2df48950fa262d14c97db3d8fd568","abstract_canon_sha256":"bed20048b724a5977f40d1426ac47872b790af5a4c1592204362bbb8ca8034e9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-03T00:05:06.164326Z","signature_b64":"lIiSfmJKpQ7yAnA/Ew4zr83Fyov4sdMKqKkyC04Cr/dpf1k1W0AmT2InhiVTCClKzm/2J/5qHaZDSMHwdyRlAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8c229886dd705b420db6be0649d6a8a8af07a133fc860cdd1d9e16a162d3371","last_reissued_at":"2026-06-03T00:05:06.163935Z","signature_status":"signed_v1","first_computed_at":"2026-06-03T00:05:06.163935Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Diagnostic Tools for Extreme Value Regression Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Ed Mackay, Jordan Richards, Philip Jonathan","submitted_at":"2026-06-01T13:45:16Z","abstract_excerpt":"Visual and quantitative goodness-of-fit diagnostics are an important tool in the practitioner's toolbox. The need for convincing and reliable diagnostics is particularly clear when fitting extreme value regression models, which are used for extrapolation far beyond the observable range of the response variable, and often evaluated at unobserved covariate values. Despite this, few diagnostics have been developed for extreme value regression models, and those available often suffer in terms of interpretability or scalability on low-dimensional or non-Euclidean covariate domains, often encountere"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.02676","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/2606.02676/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.02676","created_at":"2026-06-03T00:05:06.163990+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.02676v1","created_at":"2026-06-03T00:05:06.163990+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.02676","created_at":"2026-06-03T00:05:06.163990+00:00"},{"alias_kind":"pith_short_12","alias_value":"XDBCTCDN24C3","created_at":"2026-06-03T00:05:06.163990+00:00"},{"alias_kind":"pith_short_16","alias_value":"XDBCTCDN24C3IIG3","created_at":"2026-06-03T00:05:06.163990+00:00"},{"alias_kind":"pith_short_8","alias_value":"XDBCTCDN","created_at":"2026-06-03T00:05:06.163990+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK","json":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK.json","graph_json":"https://pith.science/api/pith-number/XDBCTCDN24C3IIG3NPQGJHLKRK/graph.json","events_json":"https://pith.science/api/pith-number/XDBCTCDN24C3IIG3NPQGJHLKRK/events.json","paper":"https://pith.science/paper/XDBCTCDN"},"agent_actions":{"view_html":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK","download_json":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK.json","view_paper":"https://pith.science/paper/XDBCTCDN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.02676&json=true","fetch_graph":"https://pith.science/api/pith-number/XDBCTCDN24C3IIG3NPQGJHLKRK/graph.json","fetch_events":"https://pith.science/api/pith-number/XDBCTCDN24C3IIG3NPQGJHLKRK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK/action/storage_attestation","attest_author":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK/action/author_attestation","sign_citation":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK/action/citation_signature","submit_replication":"https://pith.science/pith/XDBCTCDN24C3IIG3NPQGJHLKRK/action/replication_record"}},"created_at":"2026-06-03T00:05:06.163990+00:00","updated_at":"2026-06-03T00:05:06.163990+00:00"}