{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:2XKI3I2E6JHZ3SYZ4VUHWSIFKI","short_pith_number":"pith:2XKI3I2E","canonical_record":{"source":{"id":"2501.04547","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-08T14:51:36Z","cross_cats_sorted":[],"title_canon_sha256":"b763d77aaa48e899862349e1b0ae3971fc4b22dd9114181483d184c45d14a90d","abstract_canon_sha256":"8842683e6d3b1cb94f1acb8bf2f621a296a269521c8438d198d93da54ee4e839"},"schema_version":"1.0"},"canonical_sha256":"d5d48da344f24f9dcb19e5687b4905522dc815d4be2df505b28ee3f0f32830b4","source":{"kind":"arxiv","id":"2501.04547","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.04547","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"arxiv_version","alias_value":"2501.04547v1","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.04547","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"pith_short_12","alias_value":"2XKI3I2E6JHZ","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"pith_short_16","alias_value":"2XKI3I2E6JHZ3SYZ","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"pith_short_8","alias_value":"2XKI3I2E","created_at":"2026-07-05T09:58:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:2XKI3I2E6JHZ3SYZ4VUHWSIFKI","target":"record","payload":{"canonical_record":{"source":{"id":"2501.04547","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-08T14:51:36Z","cross_cats_sorted":[],"title_canon_sha256":"b763d77aaa48e899862349e1b0ae3971fc4b22dd9114181483d184c45d14a90d","abstract_canon_sha256":"8842683e6d3b1cb94f1acb8bf2f621a296a269521c8438d198d93da54ee4e839"},"schema_version":"1.0"},"canonical_sha256":"d5d48da344f24f9dcb19e5687b4905522dc815d4be2df505b28ee3f0f32830b4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:58:37.142301Z","signature_b64":"g3X0RWxoBnypR1SM+Y2tMDNen3hqvUkG2jVMtNxIOFRJRHMoNA2OSXHuEEWBySfujPvgJ1ugbJ2Vg5X/I5BECA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5d48da344f24f9dcb19e5687b4905522dc815d4be2df505b28ee3f0f32830b4","last_reissued_at":"2026-07-05T09:58:37.141841Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:58:37.141841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.04547","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:58:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U9iblyqji/Mvf0xqWMdp69kBF69w4GSn3Hwi4Fb2BsNistKYBIE9ougUt+H25k/6MP01zrfdKMJBSAUn4+SjCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T05:24:30.185423Z"},"content_sha256":"65b2c694b1bdc2b5b4f39f739ecac1aa7bb46f897cc7af284ef28c03d9b7205a","schema_version":"1.0","event_id":"sha256:65b2c694b1bdc2b5b4f39f739ecac1aa7bb46f897cc7af284ef28c03d9b7205a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:2XKI3I2E6JHZ3SYZ4VUHWSIFKI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Medical artificial intelligence toolbox (MAIT): an explainable machine learning framework for binary classification, survival modelling, and regression analyses","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Anne Svane Frahm, Daniel Dawson Murray, Jens Lundgren, Maja Milojevic, Ramtin Zargari Marandi","submitted_at":"2025-01-08T14:51:36Z","abstract_excerpt":"While machine learning offers diverse techniques suitable for exploring various medical research questions, a cohesive synergistic framework can facilitate the integration and understanding of new approaches within unified model development and interpretation. We therefore introduce the Medical Artificial Intelligence Toolbox (MAIT), an explainable, open-source Python pipeline for developing and evaluating binary classification, regression, and survival models on tabular datasets. MAIT addresses key challenges (e.g., high dimensionality, class imbalance, mixed variable types, and missingness) "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.04547","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/2501.04547/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":"2026-07-05T09:58:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XSCgcAOkEWThIL0Jt0dvLTJxNd9RzOd/116+PJyWaBIF6uTx0xYuJ3+fwRHsI3VDB2rwyX0H9MF6HV9qdx2ADg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T05:24:30.185948Z"},"content_sha256":"ab5d31991495ecb7155f38167bc5b1184a0bf453855719077ab9aec9b321dcc7","schema_version":"1.0","event_id":"sha256:ab5d31991495ecb7155f38167bc5b1184a0bf453855719077ab9aec9b321dcc7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2XKI3I2E6JHZ3SYZ4VUHWSIFKI/bundle.json","state_url":"https://pith.science/pith/2XKI3I2E6JHZ3SYZ4VUHWSIFKI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2XKI3I2E6JHZ3SYZ4VUHWSIFKI/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":"2026-08-16T05:24:30Z","links":{"resolver":"https://pith.science/pith/2XKI3I2E6JHZ3SYZ4VUHWSIFKI","bundle":"https://pith.science/pith/2XKI3I2E6JHZ3SYZ4VUHWSIFKI/bundle.json","state":"https://pith.science/pith/2XKI3I2E6JHZ3SYZ4VUHWSIFKI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2XKI3I2E6JHZ3SYZ4VUHWSIFKI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2XKI3I2E6JHZ3SYZ4VUHWSIFKI","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":"8842683e6d3b1cb94f1acb8bf2f621a296a269521c8438d198d93da54ee4e839","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-08T14:51:36Z","title_canon_sha256":"b763d77aaa48e899862349e1b0ae3971fc4b22dd9114181483d184c45d14a90d"},"schema_version":"1.0","source":{"id":"2501.04547","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.04547","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"arxiv_version","alias_value":"2501.04547v1","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.04547","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"pith_short_12","alias_value":"2XKI3I2E6JHZ","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"pith_short_16","alias_value":"2XKI3I2E6JHZ3SYZ","created_at":"2026-07-05T09:58:37Z"},{"alias_kind":"pith_short_8","alias_value":"2XKI3I2E","created_at":"2026-07-05T09:58:37Z"}],"graph_snapshots":[{"event_id":"sha256:ab5d31991495ecb7155f38167bc5b1184a0bf453855719077ab9aec9b321dcc7","target":"graph","created_at":"2026-07-05T09:58:37Z","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/2501.04547/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While machine learning offers diverse techniques suitable for exploring various medical research questions, a cohesive synergistic framework can facilitate the integration and understanding of new approaches within unified model development and interpretation. We therefore introduce the Medical Artificial Intelligence Toolbox (MAIT), an explainable, open-source Python pipeline for developing and evaluating binary classification, regression, and survival models on tabular datasets. MAIT addresses key challenges (e.g., high dimensionality, class imbalance, mixed variable types, and missingness) ","authors_text":"Anne Svane Frahm, Daniel Dawson Murray, Jens Lundgren, Maja Milojevic, Ramtin Zargari Marandi","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-08T14:51:36Z","title":"Medical artificial intelligence toolbox (MAIT): an explainable machine learning framework for binary classification, survival modelling, and regression analyses"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.04547","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":"sha256:65b2c694b1bdc2b5b4f39f739ecac1aa7bb46f897cc7af284ef28c03d9b7205a","target":"record","created_at":"2026-07-05T09:58:37Z","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":"8842683e6d3b1cb94f1acb8bf2f621a296a269521c8438d198d93da54ee4e839","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-01-08T14:51:36Z","title_canon_sha256":"b763d77aaa48e899862349e1b0ae3971fc4b22dd9114181483d184c45d14a90d"},"schema_version":"1.0","source":{"id":"2501.04547","kind":"arxiv","version":1}},"canonical_sha256":"d5d48da344f24f9dcb19e5687b4905522dc815d4be2df505b28ee3f0f32830b4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d5d48da344f24f9dcb19e5687b4905522dc815d4be2df505b28ee3f0f32830b4","first_computed_at":"2026-07-05T09:58:37.141841Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:58:37.141841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"g3X0RWxoBnypR1SM+Y2tMDNen3hqvUkG2jVMtNxIOFRJRHMoNA2OSXHuEEWBySfujPvgJ1ugbJ2Vg5X/I5BECA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:58:37.142301Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.04547","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:65b2c694b1bdc2b5b4f39f739ecac1aa7bb46f897cc7af284ef28c03d9b7205a","sha256:ab5d31991495ecb7155f38167bc5b1184a0bf453855719077ab9aec9b321dcc7"],"state_sha256":"0b69c4a28793096ed92555dda5f06b2dcfbb9809c93a7f9bea7556fcdef94b23"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ECzUzY5VyyRErd9w5uQ9jdPwyQTbODmg+ef9YhVwuw4PC8TpnbBmpeomsQtjkwkeA63fmLq2DhbSb9qy6du9Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T05:24:30.190534Z","bundle_sha256":"afeccaecc273c98a831b86eb6717e4bfa57d411a89c4343d7ce924bc80aea138"}}