{"id":"W4409802238","doi":"10.1093/biomtc/ujaf041","title":"Optimal dynamic treatment regime estimation in the presence of nonadherence","year":2025,"lang":"en","type":"article","venue":"Biometrics","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; University of Waterloo; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Estimator; Robustness (evolution); Estimation; Reliability (semiconductor); Computer science; Population; Outcome (game theory); Econometrics; Process (computing); Precision medicine; Medicine; Mathematics; Statistics; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003469624,0.0001054681,0.0001718636,0.000806663,0.00002684596,0.00001623203,0.0002993073,0.0000698147,0.000009955646],"category_scores_gemma":[0.001412052,0.00007235212,0.00003721007,0.003743879,0.00007805011,0.00009391188,0.00004474911,0.0000700399,0.00000468078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001679654,"about_ca_system_score_gemma":0.00006397083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005490717,"about_ca_topic_score_gemma":0.00001419401,"domain_scores_codex":[0.9991724,0.00005854592,0.0002777227,0.0001500841,0.0002004386,0.0001408151],"domain_scores_gemma":[0.9979867,0.001403624,0.0001307183,0.0003906939,0.00007447333,0.00001379267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001120748,0.002520196,0.004714322,0.0006549321,0.0001079345,0.00004039377,0.002500576,0.001147198,0.01310124,0.6308491,0.003703726,0.3405483],"study_design_scores_gemma":[0.001522185,0.001618704,0.01534501,0.0006760112,0.0001527509,0.00001569388,0.001144899,0.1235145,0.06081808,0.791655,0.002893349,0.0006437891],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2630218,0.0003791315,0.7298267,0.0003384858,0.00008093154,0.0008761417,0.00001968197,0.0001228209,0.005334311],"genre_scores_gemma":[0.815819,0.00009908765,0.1835218,0.00001533335,0.00000231205,0.00007046336,0.000004151208,0.000005059787,0.0004628779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5527972,"threshold_uncertainty_score":0.2950433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1184724644371154,"score_gpt":0.4363638841518298,"score_spread":0.3178914197147145,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}