{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:Q5RQ54S7NQWOR4SXPDLNGWKG7Q","short_pith_number":"pith:Q5RQ54S7","canonical_record":{"source":{"id":"2602.07884","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-08T09:32:24Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"04d8799b10c37641db3ca92f14ce95f505d95db4f1f4cef76c93e57382a74c0b","abstract_canon_sha256":"cd1c7a748d2dfd3263eecc459077e272a3305393c9a8401f7f405d24f00b9587"},"schema_version":"1.0"},"canonical_sha256":"87630ef25f6c2ce8f25778d6d35946fc3b96052f76edc9ffa522945854d29937","source":{"kind":"arxiv","id":"2602.07884","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.07884","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"arxiv_version","alias_value":"2602.07884v2","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.07884","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"pith_short_12","alias_value":"Q5RQ54S7NQWO","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"pith_short_16","alias_value":"Q5RQ54S7NQWOR4SX","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"pith_short_8","alias_value":"Q5RQ54S7","created_at":"2026-05-20T00:04:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:Q5RQ54S7NQWOR4SXPDLNGWKG7Q","target":"record","payload":{"canonical_record":{"source":{"id":"2602.07884","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-08T09:32:24Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"04d8799b10c37641db3ca92f14ce95f505d95db4f1f4cef76c93e57382a74c0b","abstract_canon_sha256":"cd1c7a748d2dfd3263eecc459077e272a3305393c9a8401f7f405d24f00b9587"},"schema_version":"1.0"},"canonical_sha256":"87630ef25f6c2ce8f25778d6d35946fc3b96052f76edc9ffa522945854d29937","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:04:24.777194Z","signature_b64":"FIB8WF44Ipp8jGRetooU53DyIgqjaMybBLgbhE5dCEnHObNU5GR1WbN2lEiVbfZ/hpA1/1GWyrXNbC+KxuUZCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"87630ef25f6c2ce8f25778d6d35946fc3b96052f76edc9ffa522945854d29937","last_reissued_at":"2026-05-20T00:04:24.776153Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:04:24.776153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2602.07884","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":"2026-05-20T00:04:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sVCucI+lZnwRYFr6IJrWYsCjQm5Mbae7f6emwcylPf5eOc8jd0CG7sT5Bh5sRF1ZaJbcqmfInLTbUUq9hVALAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T10:15:11.021289Z"},"content_sha256":"cefe06803fe59dfe932d2ee0d40032882eaca67007c520669ee779c9d120b032","schema_version":"1.0","event_id":"sha256:cefe06803fe59dfe932d2ee0d40032882eaca67007c520669ee779c9d120b032"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:Q5RQ54S7NQWOR4SXPDLNGWKG7Q","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GRAFT: Decoupling Ranking and Calibration for Survival Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Mohammad Ashhad, Ricardo Henao, Robert Hoehndorf","submitted_at":"2026-02-08T09:32:24Z","abstract_excerpt":"Survival analysis is complicated by censored data, high-dimensional features, and non-linear interactions. Classical models offer interpretability and superior calibration but are restricted to linear or predefined functional forms, while deep learning models are flexible and achieve strong discriminative performance, but tend to produce poorly calibrated survival estimates. To address this trade-off, we propose GRAFT (Gated Residual Accelerated Failure Time), a novel AFT model that decouples prognostic ranking from survival calibration. GRAFT's hybrid architecture combines a linear AFT model "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.07884","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/2602.07884/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":"2026-05-20T00:04:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3W0uW6HR1vykRFgh4exoFfjsuWjpkloqhUe0I9xGq2lVPGbEfeyAh+DDyxraY1svcr0XuvT5U2adLTEKNzVJCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T10:15:11.022121Z"},"content_sha256":"cb6796f98b0a8595e0f7b1fb580fe225cfad5f9b056aec0cf4becace69443f47","schema_version":"1.0","event_id":"sha256:cb6796f98b0a8595e0f7b1fb580fe225cfad5f9b056aec0cf4becace69443f47"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Q5RQ54S7NQWOR4SXPDLNGWKG7Q/bundle.json","state_url":"https://pith.science/pith/Q5RQ54S7NQWOR4SXPDLNGWKG7Q/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Q5RQ54S7NQWOR4SXPDLNGWKG7Q/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":"2026-06-10T10:15:11Z","links":{"resolver":"https://pith.science/pith/Q5RQ54S7NQWOR4SXPDLNGWKG7Q","bundle":"https://pith.science/pith/Q5RQ54S7NQWOR4SXPDLNGWKG7Q/bundle.json","state":"https://pith.science/pith/Q5RQ54S7NQWOR4SXPDLNGWKG7Q/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Q5RQ54S7NQWOR4SXPDLNGWKG7Q/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:Q5RQ54S7NQWOR4SXPDLNGWKG7Q","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":"cd1c7a748d2dfd3263eecc459077e272a3305393c9a8401f7f405d24f00b9587","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-08T09:32:24Z","title_canon_sha256":"04d8799b10c37641db3ca92f14ce95f505d95db4f1f4cef76c93e57382a74c0b"},"schema_version":"1.0","source":{"id":"2602.07884","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.07884","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"arxiv_version","alias_value":"2602.07884v2","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.07884","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"pith_short_12","alias_value":"Q5RQ54S7NQWO","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"pith_short_16","alias_value":"Q5RQ54S7NQWOR4SX","created_at":"2026-05-20T00:04:24Z"},{"alias_kind":"pith_short_8","alias_value":"Q5RQ54S7","created_at":"2026-05-20T00:04:24Z"}],"graph_snapshots":[{"event_id":"sha256:cb6796f98b0a8595e0f7b1fb580fe225cfad5f9b056aec0cf4becace69443f47","target":"graph","created_at":"2026-05-20T00:04:24Z","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/2602.07884/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Survival analysis is complicated by censored data, high-dimensional features, and non-linear interactions. Classical models offer interpretability and superior calibration but are restricted to linear or predefined functional forms, while deep learning models are flexible and achieve strong discriminative performance, but tend to produce poorly calibrated survival estimates. To address this trade-off, we propose GRAFT (Gated Residual Accelerated Failure Time), a novel AFT model that decouples prognostic ranking from survival calibration. GRAFT's hybrid architecture combines a linear AFT model ","authors_text":"Mohammad Ashhad, Ricardo Henao, Robert Hoehndorf","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-08T09:32:24Z","title":"GRAFT: Decoupling Ranking and Calibration for Survival Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.07884","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:cefe06803fe59dfe932d2ee0d40032882eaca67007c520669ee779c9d120b032","target":"record","created_at":"2026-05-20T00:04:24Z","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":"cd1c7a748d2dfd3263eecc459077e272a3305393c9a8401f7f405d24f00b9587","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-08T09:32:24Z","title_canon_sha256":"04d8799b10c37641db3ca92f14ce95f505d95db4f1f4cef76c93e57382a74c0b"},"schema_version":"1.0","source":{"id":"2602.07884","kind":"arxiv","version":2}},"canonical_sha256":"87630ef25f6c2ce8f25778d6d35946fc3b96052f76edc9ffa522945854d29937","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"87630ef25f6c2ce8f25778d6d35946fc3b96052f76edc9ffa522945854d29937","first_computed_at":"2026-05-20T00:04:24.776153Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:04:24.776153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FIB8WF44Ipp8jGRetooU53DyIgqjaMybBLgbhE5dCEnHObNU5GR1WbN2lEiVbfZ/hpA1/1GWyrXNbC+KxuUZCw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:04:24.777194Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.07884","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cefe06803fe59dfe932d2ee0d40032882eaca67007c520669ee779c9d120b032","sha256:cb6796f98b0a8595e0f7b1fb580fe225cfad5f9b056aec0cf4becace69443f47"],"state_sha256":"aa1dacc0c482e085faabf22beabb5d0d62162e5f5b7458bd10b489c16be16687"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kHHeo4h7lO56svPPH7G3Sg7pf5h3SLOfqE1nMF4xWLLS9Sl3+zlKU+8Cn6EqlofbigM3tbWzxKWm+s0DnkHBDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T10:15:11.026496Z","bundle_sha256":"1e0c542602aaddbfad9ea70651513cfe871cc4cfb2eaac8cb3abd894b678d515"}}