{"id":"W6901871410","doi":"10.6084/m9.figshare.16909642","title":"Additional file 6 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":"Medical Coding and Health Information","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Data quality; Coding (social sciences); General practice; Health records; Health data; Data collection; Quality (philosophy); 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":[0.007052707,0.0006495905,0.0007475067,0.003208314,0.0009297348,0.001431979,0.001574615,0.001004539,0.7957954],"category_scores_gemma":[0.1197305,0.000500333,0.001035524,0.004903192,0.0002818567,0.001734163,0.001299929,0.0008238181,0.07501705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001782372,"about_ca_system_score_gemma":0.003164672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01407472,"about_ca_topic_score_gemma":0.02096735,"domain_scores_codex":[0.9960044,0.00105643,0.001247805,0.0004358291,0.001007591,0.0002479966],"domain_scores_gemma":[0.8350669,0.1282457,0.01093954,0.005937728,0.01855628,0.001253865],"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":[0.0004150175,0.000128957,0.006055946,0.002003105,0.00006792843,0.0000406268,0.00010633,0.0003515471,0.00005152678,0.0006256551,0.9800277,0.0101257],"study_design_scores_gemma":[0.0116914,0.0007790145,0.1892938,0.00897501,0.0005757547,0.0006639471,0.001719047,0.005653144,0.001512783,0.009878581,0.7689744,0.0002831439],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.0005901963,0.000008815045,0.0003334818,0.0001955005,0.00001749097,0.0003732449,0.996874,0.0001384254,0.001468876],"genre_scores_gemma":[0.02052362,0.00009964387,0.007355902,0.0008749682,0.0001696173,0.00853228,0.9496868,0.0006335088,0.01212376],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7957954,"threshold_uncertainty_score":0.2912731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7108694782500007,"score_gpt":0.6277856902109716,"score_spread":0.08308378803902905,"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."}}