{"id":"W2624445525","doi":"10.1016/j.jclinepi.2017.06.003","title":"Graphic report of the results from propensity score method analyses","year":2017,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; Jewish General Hospital","funders":"Fonds de Recherche du Québec-Société et Culture; Jewish General Hospital","keywords":"Propensity score matching; Statistics; Medicine; Computer science; Medical physics; Mathematics","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.04915585,0.0001700011,0.003037229,0.00006500244,0.0001435619,0.000009105475,0.001252941,0.000397088,0.00001942282],"category_scores_gemma":[0.6426695,0.00008714458,0.001114526,0.00007288212,0.000855386,0.0001912078,0.0003643814,0.0013065,0.000001218798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001814651,"about_ca_system_score_gemma":0.0002136339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001888426,"about_ca_topic_score_gemma":0.00008841261,"domain_scores_codex":[0.9863395,0.005404815,0.007411581,0.0003166804,0.000282919,0.0002444925],"domain_scores_gemma":[0.8930169,0.07620493,0.02735507,0.00230848,0.0009289407,0.0001857307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001331176,0.0004569064,0.9238691,0.00005037824,0.0008353409,0.0004111222,0.00008165767,0.00006839066,0.001459052,0.03969001,0.01522293,0.01652394],"study_design_scores_gemma":[0.0004054933,0.0001990243,0.3486481,0.0001903166,0.00016096,0.000154216,0.000008193909,0.00006888537,0.001475221,0.6481234,0.0004993673,0.0000668725],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7713411,0.00009362227,0.2153194,0.01001403,0.00112011,0.0002436349,0.00002520279,0.0000278623,0.001815018],"genre_scores_gemma":[0.6371338,0.0001875132,0.3617394,0.0004056994,0.0004214563,0.000001337067,0.000001011213,0.00001173317,0.00009807732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6084334,"threshold_uncertainty_score":0.9790941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8981984549665861,"score_gpt":0.6914254145489367,"score_spread":0.2067730404176494,"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."}}