{"id":"W4388290823","doi":"10.1101/2023.11.01.23297949","title":"Cost-utility analysis of low-dose pioglitazone in a population with prediabetes and a history of stroke and TIA","year":2023,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Diabetes Treatment and Management","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Pioglitazone; Medicine; Stroke (engine); Prediabetes; Population; Insulin resistance; Diabetes mellitus; Internal medicine; Type 2 diabetes; Emergency medicine; Environmental health; Endocrinology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005263405,0.0007722699,0.001208007,0.001383266,0.000341081,0.001246355,0.00122662,0.0009940591,0.003090932],"category_scores_gemma":[0.01454704,0.0005454149,0.002973035,0.001113144,0.000486422,0.0007294971,0.0008172987,0.001085674,0.0001312023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00393594,"about_ca_system_score_gemma":0.002358973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01545167,"about_ca_topic_score_gemma":0.006295523,"domain_scores_codex":[0.9982175,0.001308884,0.00005345345,0.000147354,0.0001045382,0.0001682929],"domain_scores_gemma":[0.9913612,0.007396822,0.0005208806,0.0002022808,0.0002751909,0.0002435755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.005339137,0.0008398836,0.02826604,0.0002731453,0.001923575,0.000668534,0.00005672554,0.9485701,0.0004295187,0.004961132,0.0006984042,0.007973756],"study_design_scores_gemma":[0.0007774343,0.001441066,0.01160637,0.00007690715,0.00170998,0.0002334622,0.0001108232,0.9790493,0.0002908245,0.004197865,0.0004526382,0.00005331878],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779946,0.001222578,0.01581761,0.0007277023,0.00003256347,0.0004003123,0.001756666,0.00003430468,0.002013708],"genre_scores_gemma":[0.9969989,0.0001604002,0.001934013,0.00004940093,0.000007257738,0.0001160634,0.0004125766,0.00000274824,0.000318592],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01545167,"threshold_uncertainty_score":0.03072345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03484540637919861,"score_gpt":0.2679267891368218,"score_spread":0.2330813827576232,"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."}}