{"id":"W1534864278","doi":"10.1111/j.1360-0443.2009.02896.x","title":"Modeling missing binary outcome data in a successful web‐based smokeless tobacco cessation program","year":2010,"lang":"en","type":"article","venue":"Addiction","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"Missing data; Imputation (statistics); Abstinence; Smokeless tobacco; Randomized controlled trial; Attrition; Medicine; Smoking cessation; Statistics; Environmental health; Psychiatry; Mathematics; Tobacco use","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.1037578,0.0008518992,0.002255633,0.001662626,0.0007077617,0.00178309,0.002757756,0.001983708,0.002379091],"category_scores_gemma":[0.2425948,0.0009163722,0.002610916,0.001560282,0.00124392,0.001844873,0.0016466,0.002331997,0.0001661683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001580963,"about_ca_system_score_gemma":0.00346213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005184512,"about_ca_topic_score_gemma":0.005739031,"domain_scores_codex":[0.9531827,0.04280118,0.0007590785,0.001164943,0.001550806,0.0005413294],"domain_scores_gemma":[0.6807141,0.30029,0.0114766,0.00414139,0.002601225,0.0007766217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0191387,0.004793475,0.1391829,0.004017259,0.008576685,0.0003896317,0.00171918,0.4434119,0.0004434922,0.02613012,0.003290841,0.3489058],"study_design_scores_gemma":[0.003344135,0.003618213,0.0211268,0.0009331139,0.002511601,0.0001363921,0.000338211,0.9234208,0.0009043385,0.04213368,0.00143018,0.0001024038],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5883412,0.003293542,0.3980578,0.004245303,0.0002292394,0.002519365,0.0008438168,0.0003458141,0.00212393],"genre_scores_gemma":[0.8527744,0.001113789,0.1401902,0.0005354201,0.0001178784,0.003748457,0.0004531025,0.00003829828,0.001028414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1037578,"threshold_uncertainty_score":0.54873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1909148593675436,"score_gpt":0.4403831945771234,"score_spread":0.2494683352095798,"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."}}