{"id":"W2018472295","doi":"10.1007/s12561-013-9103-z","title":"Q-Learning: Flexible Learning About Useful Utilities","year":2013,"lang":"en","type":"article","venue":"Statistics in Biosciences","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":110,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Observational study; Machine learning; Biostatistics; Computer science; Covariate; Linear model; Artificial intelligence; Econometrics; Mathematical optimization; Mathematics; Statistics; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004624089,0.0001883482,0.0002515057,0.0002080249,0.0002247158,0.0001704268,0.0003769468,0.00008348388,0.000736755],"category_scores_gemma":[0.003792973,0.0001632762,0.0000250266,0.0004442045,0.0006029133,0.0004051474,0.000124647,0.0004420472,0.0001021344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000708594,"about_ca_system_score_gemma":0.00007693613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002068564,"about_ca_topic_score_gemma":0.00008362322,"domain_scores_codex":[0.9982193,0.0001289541,0.0004049153,0.000344411,0.0004105313,0.0004919608],"domain_scores_gemma":[0.9981221,0.001248484,0.00018505,0.0001971342,0.0001590748,0.00008814776],"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":[0.000005126725,0.00009315108,0.05558215,0.0001153395,0.000006497476,0.00001070485,0.003080875,0.00010332,0.001919396,0.9150398,0.004189669,0.01985399],"study_design_scores_gemma":[0.00009527897,0.0002606748,0.01005022,0.00008440084,0.000004569432,0.000003647978,0.003882267,0.003666399,0.003100653,0.9755664,0.003001604,0.0002839161],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4655737,0.0002074877,0.4764689,0.0003092836,0.0005605749,0.001039554,0.00005815048,0.001892074,0.05389022],"genre_scores_gemma":[0.7288471,0.0001443441,0.2654428,0.00004480861,0.00002703538,0.00006616394,0.000005160181,0.00001781161,0.005404806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2632734,"threshold_uncertainty_score":0.8066951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1224448115109042,"score_gpt":0.4082436045637552,"score_spread":0.2857987930528511,"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."}}