{"id":"W2900937465","doi":"10.1097/mlr.0000000000001014","title":"Lasso Regression for the Prediction of Intermediate Outcomes Related to Cardiovascular Disease Prevention Using the TRANSIT Quality Indicators","year":2018,"lang":"en","type":"article","venue":"Medical Care","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Sanofi (Canada); Université de Montréal","funders":"","keywords":"Dyslipidemia; Medicine; Population; Diabetes mellitus; Disease; Physical therapy; Internal medicine; Environmental health","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":[0.001294567,0.0001301481,0.0002839081,0.00005891058,0.0001671646,0.000009334053,0.0003134122,0.0001482584,0.00004927892],"category_scores_gemma":[0.00323028,0.0000647499,0.0003201554,0.0002143017,0.0002680262,0.00006793677,0.00008373921,0.000212312,0.000001123698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008677242,"about_ca_system_score_gemma":0.00009701269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000182712,"about_ca_topic_score_gemma":0.00002376953,"domain_scores_codex":[0.998105,0.0002639535,0.0004470417,0.0002094345,0.0008021615,0.0001724343],"domain_scores_gemma":[0.9982854,0.0006288185,0.000151825,0.0006020335,0.0001942015,0.0001377444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001464512,0.0008185781,0.1325301,0.003934574,0.004373427,0.00003060744,0.09572712,0.0002266933,0.001856342,0.0478266,0.004623463,0.7065879],"study_design_scores_gemma":[0.007564753,0.002699147,0.454397,0.007929379,0.007333917,0.00002077984,0.02702785,0.01255806,0.03438332,0.4102316,0.03406843,0.001785695],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7013197,0.0003277,0.295895,0.0005625968,0.0003383076,0.001258767,0.00008503987,0.0001587002,0.00005421898],"genre_scores_gemma":[0.99783,0.00002216657,0.001775874,0.00008494251,0.00009099796,0.0001231738,0.00001693238,0.00002076716,0.00003513181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7048022,"threshold_uncertainty_score":0.386718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1489838965922129,"score_gpt":0.460383819457116,"score_spread":0.3113999228649031,"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."}}