{"id":"W4386812788","doi":"10.1016/j.ypmed.2023.107702","title":"Predicting family physician physical activity electronic medical record inputs","year":2023,"lang":"en","type":"article","venue":"Preventive Medicine","topic":"Physical Activity and Health","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Medicine; Medical record; Context (archaeology); Family medicine; Electronic medical record; Medical history; Body mass index; Physical activity; Family history; Physical therapy; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008461889,0.0003431948,0.001107327,0.0002262226,0.0002110206,0.000008080638,0.00022524,0.0001561898,0.00009401712],"category_scores_gemma":[0.0006938586,0.0002670751,0.0002318141,0.001278323,0.0003663199,0.0002194051,0.0001764383,0.001351089,0.000413379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002584804,"about_ca_system_score_gemma":0.0005132622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001995113,"about_ca_topic_score_gemma":0.00003806985,"domain_scores_codex":[0.9963852,0.000251423,0.0003135067,0.000664484,0.001367687,0.001017742],"domain_scores_gemma":[0.9980683,0.0005852812,0.0001883199,0.000424914,0.0001285995,0.0006045756],"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":[0.001686311,0.00745974,0.0142367,0.001296425,0.0009139092,0.0004176853,0.003654244,0.000003977092,0.1402324,0.004158709,0.01982049,0.8061194],"study_design_scores_gemma":[0.01976881,0.01786267,0.7578769,0.006649373,0.001544763,0.0001004098,0.001404035,0.06117895,0.02697891,0.04025299,0.06463177,0.001750391],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9699489,0.00007821243,0.0007337438,0.01467685,0.0003456297,0.0006771206,0.000008876733,0.0005445182,0.01298608],"genre_scores_gemma":[0.9922737,0.0002850434,0.00001686368,0.002537142,0.003234377,0.00008997921,0.00005590732,0.00005415955,0.001452838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.804369,"threshold_uncertainty_score":0.9999781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04289707710713134,"score_gpt":0.3635079257198922,"score_spread":0.3206108486127609,"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."}}