{"id":"W2070570347","doi":"10.5539/jmr.v7n2p90","title":"Probabilistic Analysis of Balancing Scores for Causal Inference","year":2015,"lang":"en","type":"article","venue":"Journal of Mathematics Research","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Forskningsrådet om Hälsa, Arbetsliv och Välfärd; Vetenskapsrådet","keywords":"Propensity score matching; Causal inference; Covariate; Confounding; Observational study; Outcome (game theory); Causal model; Inference","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009304725,0.0001582289,0.0009160412,0.001266347,0.00005860998,0.00005310445,0.0006301712,0.0001159071,0.00003573169],"category_scores_gemma":[0.03643068,0.0001188229,0.0002527655,0.001274161,0.0002388119,0.0002364229,0.0001543748,0.0004755724,0.000002380192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002507991,"about_ca_system_score_gemma":0.0005392057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001212546,"about_ca_topic_score_gemma":0.00004410445,"domain_scores_codex":[0.9964398,0.0001985416,0.001271682,0.0001497549,0.001539519,0.0004007015],"domain_scores_gemma":[0.986405,0.007447413,0.0008986376,0.0004763819,0.004542994,0.0002295785],"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":[0.0002668623,0.002050736,0.003395066,0.003070483,0.002297263,0.00004867458,0.01033699,0.002160311,0.01177034,0.9542069,0.008517098,0.001879261],"study_design_scores_gemma":[0.0004136505,0.0008113257,0.00009643268,0.000420578,0.0004893499,0.00001975205,0.001316103,0.01503319,0.0075422,0.9736141,0.0001074239,0.0001359202],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5146598,0.0001167785,0.4832937,0.0001417293,0.00007140528,0.0006484564,0.000025269,0.00003695534,0.001005883],"genre_scores_gemma":[0.6920053,0.00002277611,0.3077323,0.000004171345,0.0000618437,0.00002582212,0.000001581318,0.00002533539,0.0001208652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1773455,"threshold_uncertainty_score":0.9716859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5381036112364946,"score_gpt":0.5669298269646585,"score_spread":0.02882621572816391,"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."}}