{"id":"W3112659431","doi":"10.23889/ijpds.v5i5.1449","title":"Linking Health and Social Data to Assess the Performance of High Dimensional Propensity Scores","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Manitoba Health; University of Manitoba","funders":"","keywords":"Propensity score matching; Confounding; Medicine; Demography; Social deprivation; Matching (statistics); Environmental health; Psychology","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":[0.001028635,0.00006029258,0.0001377675,0.00005746433,0.0004235519,0.00009463533,0.001085915,0.00001414419,0.000006610488],"category_scores_gemma":[0.0002852016,0.00003829181,0.00001270002,0.0001354209,0.00009363143,0.000785227,0.0008601052,0.0001327205,0.000001914238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005117373,"about_ca_system_score_gemma":0.0003669982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002237234,"about_ca_topic_score_gemma":0.00002355546,"domain_scores_codex":[0.9984535,0.00002169961,0.0003141402,0.0002554193,0.0008132843,0.0001419806],"domain_scores_gemma":[0.9989902,0.00003007412,0.0002242563,0.0002144645,0.0003634464,0.0001775751],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001281075,0.0001040434,0.9373158,0.000211846,0.00006062441,0.000007215957,0.0008935875,0.0004216283,0.002424917,0.006710697,0.007146304,0.04342232],"study_design_scores_gemma":[0.0005246463,0.0002673201,0.9567662,0.0001798921,0.00001210218,0.0001630651,0.00004857164,0.03776735,0.00009236565,0.0001395111,0.003978252,0.00006071695],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9444401,0.00003061006,0.0005657054,0.05387957,0.0004890981,0.0002162192,0.0003677947,0.000006430192,0.000004419678],"genre_scores_gemma":[0.9872864,0.00002986609,0.003728501,0.007942249,0.0005501006,7.0001e-7,0.0004498462,0.000003764597,0.000008586797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04593733,"threshold_uncertainty_score":0.3257662,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2356519183680368,"score_gpt":0.4298236471267988,"score_spread":0.194171728758762,"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."}}