{"id":"W6939487201","doi":"10.6084/m9.figshare.16909627.v1","title":"Additional file 1 of Assessing the suitability of general practice electronic health records for clinical prediction model development: a data quality assessment","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Data quality; Coding (social sciences); Health records; Health data; General practice; Quality (philosophy); Data collection; Electronic health record","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006702955,0.0006266162,0.0008369875,0.002804182,0.0008074081,0.001424837,0.001461862,0.001077336,0.7331404],"category_scores_gemma":[0.1126689,0.0004729723,0.0009075164,0.004612533,0.0002679854,0.001424756,0.001272172,0.0008633401,0.05229243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001666781,"about_ca_system_score_gemma":0.003407561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007992886,"about_ca_topic_score_gemma":0.01181308,"domain_scores_codex":[0.996619,0.001009186,0.001111823,0.0004645944,0.0005943384,0.0002010823],"domain_scores_gemma":[0.8470932,0.1250658,0.00924483,0.005276289,0.01214418,0.001175729],"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":[0.000797557,0.0002280789,0.01073605,0.004630286,0.0001492001,0.00007141332,0.0001724594,0.0006918149,0.00008773424,0.001234868,0.964453,0.01674749],"study_design_scores_gemma":[0.01687574,0.001152387,0.202291,0.01397373,0.0008904361,0.0009187835,0.002144057,0.007658965,0.00167379,0.01429666,0.7377971,0.0003272707],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0007496967,0.00001128269,0.0004780137,0.0001509794,0.00001521151,0.0004114402,0.9972354,0.0001117225,0.0008363053],"genre_scores_gemma":[0.02931066,0.0001249833,0.01173086,0.0009009468,0.0001426782,0.01511009,0.9337794,0.0005536966,0.008346684],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7331404,"threshold_uncertainty_score":0.3806428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2282269989235561,"score_gpt":0.4278123435981432,"score_spread":0.1995853446745871,"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."}}