{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:EDXDZQDTXT43CG2JE63OP25OC7","short_pith_number":"pith:EDXDZQDT","canonical_record":{"source":{"id":"2409.07997","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:41:58Z","cross_cats_sorted":[],"title_canon_sha256":"69050186603fac5fd529b79c085c3dda49ba2048d9060ebdbe4d4b96ed2c11c1","abstract_canon_sha256":"af7a1505e23043908aa56af98ace85cd84f6fca1dda1e24b9acf6960e8d89f14"},"schema_version":"1.0"},"canonical_sha256":"20ee3cc073bcf9b11b4927b6e7ebae17ededb55e273d3cfa7407508c30cd9f35","source":{"kind":"arxiv","id":"2409.07997","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.07997","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"arxiv_version","alias_value":"2409.07997v1","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.07997","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_12","alias_value":"EDXDZQDTXT43","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_16","alias_value":"EDXDZQDTXT43CG2J","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_8","alias_value":"EDXDZQDT","created_at":"2026-07-05T09:06:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:EDXDZQDTXT43CG2JE63OP25OC7","target":"record","payload":{"canonical_record":{"source":{"id":"2409.07997","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:41:58Z","cross_cats_sorted":[],"title_canon_sha256":"69050186603fac5fd529b79c085c3dda49ba2048d9060ebdbe4d4b96ed2c11c1","abstract_canon_sha256":"af7a1505e23043908aa56af98ace85cd84f6fca1dda1e24b9acf6960e8d89f14"},"schema_version":"1.0"},"canonical_sha256":"20ee3cc073bcf9b11b4927b6e7ebae17ededb55e273d3cfa7407508c30cd9f35","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:06:18.579903Z","signature_b64":"Bbee0OfIPglV0Kg8m2UfeJ/OPSDN+vKJ8AY7OIApQGvlUuiBIrIXb7fzkY0fAehikaOApPmZxv5eBIjnSl/EAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20ee3cc073bcf9b11b4927b6e7ebae17ededb55e273d3cfa7407508c30cd9f35","last_reissued_at":"2026-07-05T09:06:18.579456Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:06:18.579456Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.07997","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":"2026-07-05T09:06:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eH/rY/ZR80L1CMhbgQyrlJ6ULQ/SCdNuLEcgLGvL/hVdTBluZHcivpGHBp4JcCNNWdf6GTClic5ewO8tRr+aBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T01:05:06.461905Z"},"content_sha256":"975e4f0d35c386d44b2d885f5b5ce08a115d327636401bf89190838fc58e0a28","schema_version":"1.0","event_id":"sha256:975e4f0d35c386d44b2d885f5b5ce08a115d327636401bf89190838fc58e0a28"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:EDXDZQDTXT43CG2JE63OP25OC7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Privacy-preserving federated prediction of pain intensity change based on multi-center survey data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Andr\\'e Hajek, Dorte T. Gr{\\o}nne, Ewa M. Roos, Hans-Helmut K\\\"onig, Jan Baumbacha, Linda Baumbach, Mahdie Rafie, Md Shihab Ullaha, Niklas Probul, Paula Kammer, S{\\o}ren T. Skou, Supratim Das","submitted_at":"2024-09-12T12:41:58Z","abstract_excerpt":"Background: Patient-reported survey data are used to train prognostic models aimed at improving healthcare. However, such data are typically available multi-centric and, for privacy reasons, cannot easily be centralized in one data repository. Models trained locally are less accurate, robust, and generalizable. We present and apply privacy-preserving federated machine learning techniques for prognostic model building, where local survey data never leaves the legally safe harbors of the medical centers. Methods: We used centralized, local, and federated learning techniques on two healthcare dat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.07997","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/2409.07997/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":"2026-07-05T09:06:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8ZSbgp5NhNF2tU1BCgfBbaonJtu6onkQLJo8sbAef7cXQbsuB/bezseY806tF187akVt5c1TkaKwzVs1kLZ7AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T01:05:06.462435Z"},"content_sha256":"886b43885e0a9d0ff241433b310079f34fa3a27ad730e5715542ee7fd1f8b4fd","schema_version":"1.0","event_id":"sha256:886b43885e0a9d0ff241433b310079f34fa3a27ad730e5715542ee7fd1f8b4fd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EDXDZQDTXT43CG2JE63OP25OC7/bundle.json","state_url":"https://pith.science/pith/EDXDZQDTXT43CG2JE63OP25OC7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EDXDZQDTXT43CG2JE63OP25OC7/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":"2026-08-23T01:05:06Z","links":{"resolver":"https://pith.science/pith/EDXDZQDTXT43CG2JE63OP25OC7","bundle":"https://pith.science/pith/EDXDZQDTXT43CG2JE63OP25OC7/bundle.json","state":"https://pith.science/pith/EDXDZQDTXT43CG2JE63OP25OC7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EDXDZQDTXT43CG2JE63OP25OC7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:EDXDZQDTXT43CG2JE63OP25OC7","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":"af7a1505e23043908aa56af98ace85cd84f6fca1dda1e24b9acf6960e8d89f14","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:41:58Z","title_canon_sha256":"69050186603fac5fd529b79c085c3dda49ba2048d9060ebdbe4d4b96ed2c11c1"},"schema_version":"1.0","source":{"id":"2409.07997","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.07997","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"arxiv_version","alias_value":"2409.07997v1","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.07997","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_12","alias_value":"EDXDZQDTXT43","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_16","alias_value":"EDXDZQDTXT43CG2J","created_at":"2026-07-05T09:06:18Z"},{"alias_kind":"pith_short_8","alias_value":"EDXDZQDT","created_at":"2026-07-05T09:06:18Z"}],"graph_snapshots":[{"event_id":"sha256:886b43885e0a9d0ff241433b310079f34fa3a27ad730e5715542ee7fd1f8b4fd","target":"graph","created_at":"2026-07-05T09:06:18Z","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/2409.07997/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Background: Patient-reported survey data are used to train prognostic models aimed at improving healthcare. However, such data are typically available multi-centric and, for privacy reasons, cannot easily be centralized in one data repository. Models trained locally are less accurate, robust, and generalizable. We present and apply privacy-preserving federated machine learning techniques for prognostic model building, where local survey data never leaves the legally safe harbors of the medical centers. Methods: We used centralized, local, and federated learning techniques on two healthcare dat","authors_text":"Andr\\'e Hajek, Dorte T. Gr{\\o}nne, Ewa M. Roos, Hans-Helmut K\\\"onig, Jan Baumbacha, Linda Baumbach, Mahdie Rafie, Md Shihab Ullaha, Niklas Probul, Paula Kammer, S{\\o}ren T. Skou, Supratim Das","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:41:58Z","title":"Privacy-preserving federated prediction of pain intensity change based on multi-center survey data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.07997","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":"sha256:975e4f0d35c386d44b2d885f5b5ce08a115d327636401bf89190838fc58e0a28","target":"record","created_at":"2026-07-05T09:06:18Z","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":"af7a1505e23043908aa56af98ace85cd84f6fca1dda1e24b9acf6960e8d89f14","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-12T12:41:58Z","title_canon_sha256":"69050186603fac5fd529b79c085c3dda49ba2048d9060ebdbe4d4b96ed2c11c1"},"schema_version":"1.0","source":{"id":"2409.07997","kind":"arxiv","version":1}},"canonical_sha256":"20ee3cc073bcf9b11b4927b6e7ebae17ededb55e273d3cfa7407508c30cd9f35","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"20ee3cc073bcf9b11b4927b6e7ebae17ededb55e273d3cfa7407508c30cd9f35","first_computed_at":"2026-07-05T09:06:18.579456Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:06:18.579456Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bbee0OfIPglV0Kg8m2UfeJ/OPSDN+vKJ8AY7OIApQGvlUuiBIrIXb7fzkY0fAehikaOApPmZxv5eBIjnSl/EAw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:06:18.579903Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.07997","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:975e4f0d35c386d44b2d885f5b5ce08a115d327636401bf89190838fc58e0a28","sha256:886b43885e0a9d0ff241433b310079f34fa3a27ad730e5715542ee7fd1f8b4fd"],"state_sha256":"f1705ab20a17555fb8b6db12d50c88780538f4a9e5bd4d6bf7c5edf814f68446"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"66aq+OX+fsvYmhAqMagUDQCSBftxbjXPkE3k1wCIdP79bRZjiaWYFh9zoKyTpfhNNJ04jj9JqKbOMmX7C34PBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T01:05:06.470149Z","bundle_sha256":"e49d95842ae42fb1748208cbe2731e9598a0896358fc17309d142fe9fedd1b20"}}