{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:I3FR2PTBVLHGQLFRFPSVVPW7R7","short_pith_number":"pith:I3FR2PTB","canonical_record":{"source":{"id":"2606.25762","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:37:36Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"66dbbdcf67aaaad58dff3bbaa8da1cabeb277ef81f4d1cc355e675179c28dfed","abstract_canon_sha256":"8f6f0aef0a4b52094abcc54422229a877c3c0c068706d70bc2d9a1c5e1cad5f6"},"schema_version":"1.0"},"canonical_sha256":"46cb1d3e61aace682cb12be55abedf8ffe77bb291ee0ffc2e4dc1f4fa9130c79","source":{"kind":"arxiv","id":"2606.25762","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25762","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25762v1","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25762","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_12","alias_value":"I3FR2PTBVLHG","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_16","alias_value":"I3FR2PTBVLHGQLFR","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_8","alias_value":"I3FR2PTB","created_at":"2026-06-25T01:18:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:I3FR2PTBVLHGQLFRFPSVVPW7R7","target":"record","payload":{"canonical_record":{"source":{"id":"2606.25762","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:37:36Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"66dbbdcf67aaaad58dff3bbaa8da1cabeb277ef81f4d1cc355e675179c28dfed","abstract_canon_sha256":"8f6f0aef0a4b52094abcc54422229a877c3c0c068706d70bc2d9a1c5e1cad5f6"},"schema_version":"1.0"},"canonical_sha256":"46cb1d3e61aace682cb12be55abedf8ffe77bb291ee0ffc2e4dc1f4fa9130c79","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T01:18:14.585759Z","signature_b64":"vMRIcTsFM/8U2sBblzHtkAJxW1rgr3Z8891WkqJp7e5vnW6z26D3IBFm9A+EKVGI+CZO4ClCIOWCP2M0V7MSAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"46cb1d3e61aace682cb12be55abedf8ffe77bb291ee0ffc2e4dc1f4fa9130c79","last_reissued_at":"2026-06-25T01:18:14.585416Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T01:18:14.585416Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.25762","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":"2026-06-25T01:18:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T2SziSDTPNSxT/y2Zr06m0ADOqbRK9of6lmCrBqy4NegkwHEbdLJ/I6a7oZpBHciGt2eO82sbUVy1P2wI7mYDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T13:42:16.408340Z"},"content_sha256":"ba35732b092897c4bc0ac2c572df74cfd975e58238ab9a5efee6f7081f383929","schema_version":"1.0","event_id":"sha256:ba35732b092897c4bc0ac2c572df74cfd975e58238ab9a5efee6f7081f383929"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:I3FR2PTBVLHGQLFRFPSVVPW7R7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"OncoSynth: Synthetic data generation for treatment effect estimation in oncology","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Dennis Frauen, Harry Amad, Julian Welzel, Maresa Schr\\\"oder, Marie Brockschmidt, Mihaela van der Schaar, Octavia-Andreea Ciora, Stefan Feuerriegel, Thomas Callender","submitted_at":"2026-06-24T12:37:36Z","abstract_excerpt":"In oncology, access to patient-level data is often restricted. Synthetic data provides an alternative for analyzing treatment effectiveness, but existing methods for synthetic data generation fail to preserve the causal relationships between covariates, treatments, and outcomes, thereby leading to biased estimates of treatment effects. Here, we introduce OncoSynth, a generative, causally-aware machine learning framework designed to produce synthetic cohorts that enable accurate estimation of population- and patient-level treatment effects. OncoSynth uses a diffusion-based sequential approach t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25762","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/2606.25762/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":"2026-06-25T01:18:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vs229xwIpz2Ahq4Fu5arYuzGKPKSktvxtVWWMUblAIOAjk0+/pd1BuDA/QLdOx5u4C4w9zzTvMTFjSk1MSVaBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-01T13:42:16.408731Z"},"content_sha256":"c5503fcd1b88d04a3a593f10c9a48f5c41f47e74a5c8a084bfb945769a4e41c6","schema_version":"1.0","event_id":"sha256:c5503fcd1b88d04a3a593f10c9a48f5c41f47e74a5c8a084bfb945769a4e41c6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I3FR2PTBVLHGQLFRFPSVVPW7R7/bundle.json","state_url":"https://pith.science/pith/I3FR2PTBVLHGQLFRFPSVVPW7R7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I3FR2PTBVLHGQLFRFPSVVPW7R7/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":"2026-07-01T13:42:16Z","links":{"resolver":"https://pith.science/pith/I3FR2PTBVLHGQLFRFPSVVPW7R7","bundle":"https://pith.science/pith/I3FR2PTBVLHGQLFRFPSVVPW7R7/bundle.json","state":"https://pith.science/pith/I3FR2PTBVLHGQLFRFPSVVPW7R7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I3FR2PTBVLHGQLFRFPSVVPW7R7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:I3FR2PTBVLHGQLFRFPSVVPW7R7","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":"8f6f0aef0a4b52094abcc54422229a877c3c0c068706d70bc2d9a1c5e1cad5f6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:37:36Z","title_canon_sha256":"66dbbdcf67aaaad58dff3bbaa8da1cabeb277ef81f4d1cc355e675179c28dfed"},"schema_version":"1.0","source":{"id":"2606.25762","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25762","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25762v1","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25762","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_12","alias_value":"I3FR2PTBVLHG","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_16","alias_value":"I3FR2PTBVLHGQLFR","created_at":"2026-06-25T01:18:14Z"},{"alias_kind":"pith_short_8","alias_value":"I3FR2PTB","created_at":"2026-06-25T01:18:14Z"}],"graph_snapshots":[{"event_id":"sha256:c5503fcd1b88d04a3a593f10c9a48f5c41f47e74a5c8a084bfb945769a4e41c6","target":"graph","created_at":"2026-06-25T01:18:14Z","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/2606.25762/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In oncology, access to patient-level data is often restricted. Synthetic data provides an alternative for analyzing treatment effectiveness, but existing methods for synthetic data generation fail to preserve the causal relationships between covariates, treatments, and outcomes, thereby leading to biased estimates of treatment effects. Here, we introduce OncoSynth, a generative, causally-aware machine learning framework designed to produce synthetic cohorts that enable accurate estimation of population- and patient-level treatment effects. OncoSynth uses a diffusion-based sequential approach t","authors_text":"Dennis Frauen, Harry Amad, Julian Welzel, Maresa Schr\\\"oder, Marie Brockschmidt, Mihaela van der Schaar, Octavia-Andreea Ciora, Stefan Feuerriegel, Thomas Callender","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:37:36Z","title":"OncoSynth: Synthetic data generation for treatment effect estimation in oncology"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25762","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:ba35732b092897c4bc0ac2c572df74cfd975e58238ab9a5efee6f7081f383929","target":"record","created_at":"2026-06-25T01:18:14Z","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":"8f6f0aef0a4b52094abcc54422229a877c3c0c068706d70bc2d9a1c5e1cad5f6","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T12:37:36Z","title_canon_sha256":"66dbbdcf67aaaad58dff3bbaa8da1cabeb277ef81f4d1cc355e675179c28dfed"},"schema_version":"1.0","source":{"id":"2606.25762","kind":"arxiv","version":1}},"canonical_sha256":"46cb1d3e61aace682cb12be55abedf8ffe77bb291ee0ffc2e4dc1f4fa9130c79","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"46cb1d3e61aace682cb12be55abedf8ffe77bb291ee0ffc2e4dc1f4fa9130c79","first_computed_at":"2026-06-25T01:18:14.585416Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-25T01:18:14.585416Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vMRIcTsFM/8U2sBblzHtkAJxW1rgr3Z8891WkqJp7e5vnW6z26D3IBFm9A+EKVGI+CZO4ClCIOWCP2M0V7MSAQ==","signature_status":"signed_v1","signed_at":"2026-06-25T01:18:14.585759Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.25762","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba35732b092897c4bc0ac2c572df74cfd975e58238ab9a5efee6f7081f383929","sha256:c5503fcd1b88d04a3a593f10c9a48f5c41f47e74a5c8a084bfb945769a4e41c6"],"state_sha256":"73fe27c00a2fc7f50e55ad669208ca13622a8c7a15a1dbf175f8a719f423af6d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R2cOJ1HsFiLILxdYPFhQDuP+iiBLQNh9TYR5sMGIRLMxdy+yx0/+FdzhTtEjLaa/0GcnYoZ0XFQ9rQCOdL7DAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-01T13:42:16.410941Z","bundle_sha256":"8580d10d777159b9cbd495903cebbb1944f3f55060cbda4cd61ae9d1beed2380"}}