{"id":"W2911982698","doi":"10.1503/cmaj.180841","title":"Using electronic health records for clinical trials: Where do we stand and where can we go?","year":2019,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health records; Electronic health record; Computer science; Key (lock); Data science; Health data; World Wide Web; Data mining; Health care; Computer security","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch","research_integrity"],"category_scores_codex":[0.06372546,0.0002754186,0.00148438,0.0002733053,0.001439887,0.00008132064,0.0003146389,0.001409901,0.003379824],"category_scores_gemma":[0.009267005,0.0002425914,0.0002556417,0.0003146711,0.00003943439,0.0001619434,0.00002958654,0.005006106,0.000129401],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.0128472,"about_ca_system_score_gemma":0.0933297,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01486788,"about_ca_topic_score_gemma":0.5020353,"domain_scores_codex":[0.9824597,0.009700269,0.00351345,0.0004701545,0.001205856,0.002650544],"domain_scores_gemma":[0.9857452,0.006431815,0.002547195,0.0002525726,0.0006898647,0.004333353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009452502,0.00003010517,0.2444032,0.00099303,0.0002575544,0.00001229054,0.001530519,0.000001275506,0.000001816421,0.001254281,0.5359696,0.2154518],"study_design_scores_gemma":[0.003918044,0.0005322163,0.001353047,0.002344097,0.00003609603,0.00006497478,0.0030905,0.000964634,9.560439e-8,0.001182579,0.9862866,0.0002271064],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"review","genre_scores_codex":[0.1324211,0.1847435,0.001529483,0.6566827,0.01659295,0.006091157,0.0004261183,0.00009648751,0.001416506],"genre_scores_gemma":[0.1804963,0.682036,0.002226313,0.04668082,0.05113168,0.0004477526,0.00004692717,0.0005532907,0.03638088],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.6100019,"threshold_uncertainty_score":0.9998865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1579759512906265,"score_gpt":0.5142897031455863,"score_spread":0.3563137518549598,"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."}}