{"id":"W4402012272","doi":"10.1111/dom.15899","title":"Optimizing physician‐encounter frequency for type 2 diabetes patients in primary care based on cardiovascular risk assessment: A target trial emulation study","year":2024,"lang":"en","type":"article","venue":"Diabetes Obesity and Metabolism","topic":"Primary Care and Health Outcomes","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; Bruyère; University of Ottawa","funders":"Young Scientists Fund; University of Hong Kong; National Natural Science Foundation of China","keywords":"Medicine; Type 2 diabetes; Emulation; Primary care; Risk assessment; Diabetes mellitus; Internal medicine; Family medicine; Intensive care medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01387159,0.0007336634,0.001604363,0.000253358,0.0001885134,0.0007953399,0.0008373429,0.000915657,0.002036024],"category_scores_gemma":[0.01574376,0.0003013745,0.001708742,0.0003332654,0.0005697569,0.0007399603,0.0006880032,0.001068044,0.0002242949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009721721,"about_ca_system_score_gemma":0.001490523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009017036,"about_ca_topic_score_gemma":0.0006323414,"domain_scores_codex":[0.9934077,0.005511764,0.0002271418,0.0004433184,0.0001592339,0.0002508241],"domain_scores_gemma":[0.9904572,0.005939114,0.001726779,0.0009376252,0.0003236391,0.0006155958],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.8163077,0.03796091,0.04296551,0.0008150446,0.005627045,0.0001508849,0.0003896746,0.02877524,0.003356466,0.001060802,0.001100017,0.06149076],"study_design_scores_gemma":[0.2552897,0.5844708,0.05426472,0.000112019,0.005949302,0.0001932291,0.0001822232,0.09324677,0.002809308,0.001525572,0.001860157,0.00009617049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951196,0.0003333501,0.002560341,0.0002338608,0.00004822006,0.0009770347,0.0001631119,0.00003131679,0.0005332846],"genre_scores_gemma":[0.9961208,0.0001163384,0.001967137,0.0001832749,0.00005317529,0.001080499,0.0002095248,0.000005455581,0.000263902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01387159,"threshold_uncertainty_score":0.07336086,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02478251503964235,"score_gpt":0.3467474885368992,"score_spread":0.3219649734972568,"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."}}