{"id":"W2609332150","doi":"10.1177/1460458217704244","title":"Extended use of electronic health records by primary care physicians: Does the electronic health record artefact matter?","year":2017,"lang":"en","type":"article","venue":"Health Informatics Journal","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal; Université du Québec à Trois-Rivières","funders":"","keywords":"Electronic health record; Health records; Software deployment; Electronic medical record; Medical record; Family medicine; Clinical decision support system; Primary care; Health care; Medicine; Population; Population health; Perspective (graphical); Medical emergency; Computer science; Decision support system; Environmental health; Data mining","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","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01163058,0.0008067855,0.002378101,0.0004097989,0.01173615,0.0002982081,0.00190978,0.0004163561,0.0002297116],"category_scores_gemma":[0.0003792413,0.0005504063,0.0004170025,0.0003904866,0.0002844073,0.00190063,0.0003161489,0.007507973,0.0002699259],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.01338956,"about_ca_system_score_gemma":0.04048227,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008719457,"about_ca_topic_score_gemma":0.009630824,"domain_scores_codex":[0.9796741,0.003844712,0.007882756,0.0004760751,0.001532341,0.006590019],"domain_scores_gemma":[0.9764743,0.0009574009,0.01797344,0.002525493,0.0008088847,0.001260527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004388086,0.0002702784,0.03048861,0.01668397,0.0002908842,0.000001938066,0.04324597,0.00001910669,0.00000874125,0.00166941,0.4245195,0.4823628],"study_design_scores_gemma":[0.003368629,0.004236216,0.02883935,0.00583665,0.00003451896,0.0001914553,0.01648699,0.0008039824,0.000009099328,0.00156971,0.9378635,0.0007599018],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3994533,0.0736251,0.04494504,0.4075481,0.02568746,0.03446885,0.002219049,0.001034839,0.01101822],"genre_scores_gemma":[0.6809552,0.1324523,0.00422821,0.1709223,0.003639109,0.0008551746,0.0006096272,0.0005574362,0.005780592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.513344,"threshold_uncertainty_score":0.9996948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04293408546417128,"score_gpt":0.3966977606520296,"score_spread":0.3537636751878583,"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."}}