{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:DLPPRP6O7XJIUW35FX7MQHHZ67","short_pith_number":"pith:DLPPRP6O","canonical_record":{"source":{"id":"2501.17835","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-01-29T18:31:25Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"abcb438e8e210dc9bb1760740a93ec5e372c9d74e99552d8446f1a81428bbe55","abstract_canon_sha256":"6bdea501af32f10999cff6754078e5281852a0193946891143b6ebce232ea4af"},"schema_version":"1.0"},"canonical_sha256":"1adef8bfcefdd28a5b7d2dfec81cf9f7fef763e50a04fa1e84ad233a2b8294ff","source":{"kind":"arxiv","id":"2501.17835","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.17835","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"arxiv_version","alias_value":"2501.17835v2","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.17835","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"pith_short_12","alias_value":"DLPPRP6O7XJI","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"pith_short_16","alias_value":"DLPPRP6O7XJIUW35","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"pith_short_8","alias_value":"DLPPRP6O","created_at":"2026-06-10T01:08:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:DLPPRP6O7XJIUW35FX7MQHHZ67","target":"record","payload":{"canonical_record":{"source":{"id":"2501.17835","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-01-29T18:31:25Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"abcb438e8e210dc9bb1760740a93ec5e372c9d74e99552d8446f1a81428bbe55","abstract_canon_sha256":"6bdea501af32f10999cff6754078e5281852a0193946891143b6ebce232ea4af"},"schema_version":"1.0"},"canonical_sha256":"1adef8bfcefdd28a5b7d2dfec81cf9f7fef763e50a04fa1e84ad233a2b8294ff","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-10T01:08:26.977565Z","signature_b64":"2K+Gan2TTaefMqZzcYBD0lHHo7uQOXVxrIf6W/zxKuAR7aoDPjlPvYXRgbleoL3s+aQPt70CfEo+/SWv5owlDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1adef8bfcefdd28a5b7d2dfec81cf9f7fef763e50a04fa1e84ad233a2b8294ff","last_reissued_at":"2026-06-10T01:08:26.976490Z","signature_status":"signed_v1","first_computed_at":"2026-06-10T01:08:26.976490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.17835","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":"2026-06-10T01:08:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jJkoYLMU1BBJpnIBpX48vuROGDCJld8Wt2fRdtcz+iRomrop61f4/GiY3X1ruJON203QcAFPveLWmQSKVoXuCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T11:44:26.500375Z"},"content_sha256":"ba66f4a223a2ec083f53397950cb035dadaede5339a515889967b102e26ec560","schema_version":"1.0","event_id":"sha256:ba66f4a223a2ec083f53397950cb035dadaede5339a515889967b102e26ec560"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:DLPPRP6O7XJIUW35FX7MQHHZ67","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Estimator-Robust Design for Augmenting Randomized Controlled Trials with External Real-World Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ME","authors_text":"Andrew Mertens, Jens Tarp, Mark van der Laan, Sky Qiu","submitted_at":"2025-01-29T18:31:25Z","abstract_excerpt":"Augmenting randomized controlled trials (RCTs) with external real-world data (RWD) has the potential to improve the finite sample efficiency of treatment effect estimators. We describe using adaptive targeted maximum likelihood estimation (A-TMLE) for estimating the average treatment effect (ATE) by decomposing the ATE estimand into two components: a pooled-ATE estimand that combines data from both the RCT and external sources, and a bias estimand that captures the conditional effect of RCT enrollment on the outcome. This approach views the RCT data as the reference and corrects for inconsiste"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.17835","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/2501.17835/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":"2026-06-10T01:08:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"frzO/D53r63OzG6qblNfxdFCc2L4uzMACRRh7ZZZ+YRvBGcECtsl+K02uPPTOqVB99ZtOu/9cn6tXd5dLkSSCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T11:44:26.501042Z"},"content_sha256":"75b1026030aa2658e60e4b250af48fbd8eb4d3e4636ffd9644a8751874aaa34e","schema_version":"1.0","event_id":"sha256:75b1026030aa2658e60e4b250af48fbd8eb4d3e4636ffd9644a8751874aaa34e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DLPPRP6O7XJIUW35FX7MQHHZ67/bundle.json","state_url":"https://pith.science/pith/DLPPRP6O7XJIUW35FX7MQHHZ67/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DLPPRP6O7XJIUW35FX7MQHHZ67/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":"2026-06-10T11:44:26Z","links":{"resolver":"https://pith.science/pith/DLPPRP6O7XJIUW35FX7MQHHZ67","bundle":"https://pith.science/pith/DLPPRP6O7XJIUW35FX7MQHHZ67/bundle.json","state":"https://pith.science/pith/DLPPRP6O7XJIUW35FX7MQHHZ67/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DLPPRP6O7XJIUW35FX7MQHHZ67/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DLPPRP6O7XJIUW35FX7MQHHZ67","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":"6bdea501af32f10999cff6754078e5281852a0193946891143b6ebce232ea4af","cross_cats_sorted":["stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-01-29T18:31:25Z","title_canon_sha256":"abcb438e8e210dc9bb1760740a93ec5e372c9d74e99552d8446f1a81428bbe55"},"schema_version":"1.0","source":{"id":"2501.17835","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.17835","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"arxiv_version","alias_value":"2501.17835v2","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.17835","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"pith_short_12","alias_value":"DLPPRP6O7XJI","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"pith_short_16","alias_value":"DLPPRP6O7XJIUW35","created_at":"2026-06-10T01:08:26Z"},{"alias_kind":"pith_short_8","alias_value":"DLPPRP6O","created_at":"2026-06-10T01:08:26Z"}],"graph_snapshots":[{"event_id":"sha256:75b1026030aa2658e60e4b250af48fbd8eb4d3e4636ffd9644a8751874aaa34e","target":"graph","created_at":"2026-06-10T01:08:26Z","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/2501.17835/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Augmenting randomized controlled trials (RCTs) with external real-world data (RWD) has the potential to improve the finite sample efficiency of treatment effect estimators. We describe using adaptive targeted maximum likelihood estimation (A-TMLE) for estimating the average treatment effect (ATE) by decomposing the ATE estimand into two components: a pooled-ATE estimand that combines data from both the RCT and external sources, and a bias estimand that captures the conditional effect of RCT enrollment on the outcome. This approach views the RCT data as the reference and corrects for inconsiste","authors_text":"Andrew Mertens, Jens Tarp, Mark van der Laan, Sky Qiu","cross_cats":["stat.AP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-01-29T18:31:25Z","title":"An Estimator-Robust Design for Augmenting Randomized Controlled Trials with External Real-World Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.17835","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:ba66f4a223a2ec083f53397950cb035dadaede5339a515889967b102e26ec560","target":"record","created_at":"2026-06-10T01:08:26Z","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":"6bdea501af32f10999cff6754078e5281852a0193946891143b6ebce232ea4af","cross_cats_sorted":["stat.AP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ME","submitted_at":"2025-01-29T18:31:25Z","title_canon_sha256":"abcb438e8e210dc9bb1760740a93ec5e372c9d74e99552d8446f1a81428bbe55"},"schema_version":"1.0","source":{"id":"2501.17835","kind":"arxiv","version":2}},"canonical_sha256":"1adef8bfcefdd28a5b7d2dfec81cf9f7fef763e50a04fa1e84ad233a2b8294ff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1adef8bfcefdd28a5b7d2dfec81cf9f7fef763e50a04fa1e84ad233a2b8294ff","first_computed_at":"2026-06-10T01:08:26.976490Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-10T01:08:26.976490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2K+Gan2TTaefMqZzcYBD0lHHo7uQOXVxrIf6W/zxKuAR7aoDPjlPvYXRgbleoL3s+aQPt70CfEo+/SWv5owlDA==","signature_status":"signed_v1","signed_at":"2026-06-10T01:08:26.977565Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.17835","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba66f4a223a2ec083f53397950cb035dadaede5339a515889967b102e26ec560","sha256:75b1026030aa2658e60e4b250af48fbd8eb4d3e4636ffd9644a8751874aaa34e"],"state_sha256":"edaa337d92d9e5109d2ddddda48a16fdbc98218444af0beb1780499711aa8adc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9Zu+S9fZ2h2RD0Q30nbk/EKGpqAnm/HxU2cRttong9Cc7UHNc2kIysKi9Dkt/sHhIELk2WsmzQ6VvbjUOhRmBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T11:44:26.504697Z","bundle_sha256":"c7d47f2e7587833420356475433315f9b8e9d344daefcac37333b7b3c8ebe442"}}