{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:BOHSEFFTZU6MNXMLDBNN2A7NKF","short_pith_number":"pith:BOHSEFFT","canonical_record":{"source":{"id":"2210.03047","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-10-06T16:52:38Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c577cb3acb22a9c8a07893ea0f20ac93343a28094c73332418f81b9d4b8d0c98","abstract_canon_sha256":"14793bf80837171e2c3b4e86dbea96c543f9c77898ec2c2b3f78fec0d0e49b0c"},"schema_version":"1.0"},"canonical_sha256":"0b8f2214b3cd3cc6dd8b185add03ed516b716ede9731a8dacfe73ed742e74835","source":{"kind":"arxiv","id":"2210.03047","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.03047","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"arxiv_version","alias_value":"2210.03047v3","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.03047","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"pith_short_12","alias_value":"BOHSEFFTZU6M","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"pith_short_16","alias_value":"BOHSEFFTZU6MNXML","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"pith_short_8","alias_value":"BOHSEFFT","created_at":"2026-07-05T06:06:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:BOHSEFFTZU6MNXMLDBNN2A7NKF","target":"record","payload":{"canonical_record":{"source":{"id":"2210.03047","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-10-06T16:52:38Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c577cb3acb22a9c8a07893ea0f20ac93343a28094c73332418f81b9d4b8d0c98","abstract_canon_sha256":"14793bf80837171e2c3b4e86dbea96c543f9c77898ec2c2b3f78fec0d0e49b0c"},"schema_version":"1.0"},"canonical_sha256":"0b8f2214b3cd3cc6dd8b185add03ed516b716ede9731a8dacfe73ed742e74835","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:06:03.653055Z","signature_b64":"Da017B4AeJwAl7IKZhSQTIpjQUuApOVMxudDbpOGzfaKvXLpzlpHpWVZ81mxGLo2+Uiqkum8IcjI0eH9ANWuCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0b8f2214b3cd3cc6dd8b185add03ed516b716ede9731a8dacfe73ed742e74835","last_reissued_at":"2026-07-05T06:06:03.652512Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:06:03.652512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.03047","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":"2026-07-05T06:06:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8+7alEEfwahVMf8G4PBQYMQuYlgfgsM+S5x8rayEIpaH3JZRH9WP4xmNUcpWp9cNyhy/UHnQT10h0n6jg80VAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:00:21.579749Z"},"content_sha256":"039ae3a6e7ec9bcc8c300ec1c1cbb54cc108e51fc3b0e53178df0a4047d0aec9","schema_version":"1.0","event_id":"sha256:039ae3a6e7ec9bcc8c300ec1c1cbb54cc108e51fc3b0e53178df0a4047d0aec9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:BOHSEFFTZU6MNXMLDBNN2A7NKF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Conditional Feature Importance for Mixed Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"David S. Watson, Kristin Blesch, Marvin N. Wright","submitted_at":"2022-10-06T16:52:38Z","abstract_excerpt":"Despite the popularity of feature importance (FI) measures in interpretable machine learning, the statistical adequacy of these methods is rarely discussed. From a statistical perspective, a major distinction is between analyzing a variable's importance before and after adjusting for covariates - i.e., between $\\textit{marginal}$ and $\\textit{conditional}$ measures. Our work draws attention to this rarely acknowledged, yet crucial distinction and showcases its implications. Further, we reveal that for testing conditional FI, only few methods are available and practitioners have hitherto been s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.03047","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/2210.03047/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":"2026-07-05T06:06:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TgnNf+I8p2lhBi+Gq0vciJi2d1cChcikX4qPuLuzt2uHttS+Rg3j5EkhsCp34/4UKk+QOdNoix29ApWSe2baAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:00:21.580295Z"},"content_sha256":"90d9714bea09be514ce89768ca499db51e3fda985f146306b74a832558e34d22","schema_version":"1.0","event_id":"sha256:90d9714bea09be514ce89768ca499db51e3fda985f146306b74a832558e34d22"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BOHSEFFTZU6MNXMLDBNN2A7NKF/bundle.json","state_url":"https://pith.science/pith/BOHSEFFTZU6MNXMLDBNN2A7NKF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BOHSEFFTZU6MNXMLDBNN2A7NKF/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":"2026-08-04T12:00:21Z","links":{"resolver":"https://pith.science/pith/BOHSEFFTZU6MNXMLDBNN2A7NKF","bundle":"https://pith.science/pith/BOHSEFFTZU6MNXMLDBNN2A7NKF/bundle.json","state":"https://pith.science/pith/BOHSEFFTZU6MNXMLDBNN2A7NKF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BOHSEFFTZU6MNXMLDBNN2A7NKF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:BOHSEFFTZU6MNXMLDBNN2A7NKF","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":"14793bf80837171e2c3b4e86dbea96c543f9c77898ec2c2b3f78fec0d0e49b0c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-10-06T16:52:38Z","title_canon_sha256":"c577cb3acb22a9c8a07893ea0f20ac93343a28094c73332418f81b9d4b8d0c98"},"schema_version":"1.0","source":{"id":"2210.03047","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.03047","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"arxiv_version","alias_value":"2210.03047v3","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.03047","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"pith_short_12","alias_value":"BOHSEFFTZU6M","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"pith_short_16","alias_value":"BOHSEFFTZU6MNXML","created_at":"2026-07-05T06:06:03Z"},{"alias_kind":"pith_short_8","alias_value":"BOHSEFFT","created_at":"2026-07-05T06:06:03Z"}],"graph_snapshots":[{"event_id":"sha256:90d9714bea09be514ce89768ca499db51e3fda985f146306b74a832558e34d22","target":"graph","created_at":"2026-07-05T06:06:03Z","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/2210.03047/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Despite the popularity of feature importance (FI) measures in interpretable machine learning, the statistical adequacy of these methods is rarely discussed. From a statistical perspective, a major distinction is between analyzing a variable's importance before and after adjusting for covariates - i.e., between $\\textit{marginal}$ and $\\textit{conditional}$ measures. Our work draws attention to this rarely acknowledged, yet crucial distinction and showcases its implications. Further, we reveal that for testing conditional FI, only few methods are available and practitioners have hitherto been s","authors_text":"David S. Watson, Kristin Blesch, Marvin N. Wright","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-10-06T16:52:38Z","title":"Conditional Feature Importance for Mixed Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.03047","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":"sha256:039ae3a6e7ec9bcc8c300ec1c1cbb54cc108e51fc3b0e53178df0a4047d0aec9","target":"record","created_at":"2026-07-05T06:06:03Z","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":"14793bf80837171e2c3b4e86dbea96c543f9c77898ec2c2b3f78fec0d0e49b0c","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2022-10-06T16:52:38Z","title_canon_sha256":"c577cb3acb22a9c8a07893ea0f20ac93343a28094c73332418f81b9d4b8d0c98"},"schema_version":"1.0","source":{"id":"2210.03047","kind":"arxiv","version":3}},"canonical_sha256":"0b8f2214b3cd3cc6dd8b185add03ed516b716ede9731a8dacfe73ed742e74835","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0b8f2214b3cd3cc6dd8b185add03ed516b716ede9731a8dacfe73ed742e74835","first_computed_at":"2026-07-05T06:06:03.652512Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:06:03.652512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Da017B4AeJwAl7IKZhSQTIpjQUuApOVMxudDbpOGzfaKvXLpzlpHpWVZ81mxGLo2+Uiqkum8IcjI0eH9ANWuCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:06:03.653055Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.03047","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:039ae3a6e7ec9bcc8c300ec1c1cbb54cc108e51fc3b0e53178df0a4047d0aec9","sha256:90d9714bea09be514ce89768ca499db51e3fda985f146306b74a832558e34d22"],"state_sha256":"fceddbfa26af08fa1c091861cac6a74de5d1e130dd1b2d404598802f4f3d6d54"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e6l7N7C7wGw2UF9jTMjJmg4fZfp5h+QrV+OksHgeU2EwPDMsmZh6+XQJeHTsK/lBNO11EEpTefD8PsSYs+uSBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T12:00:21.585670Z","bundle_sha256":"ea929193a631174407257b73dce98131ab01904812a5f686d631d1ffe5e403a7"}}