{"id":"W4387933953","doi":"10.1016/j.jcjd.2023.10.193","title":"DEVELOPMENT OF DIABETES HEALTH LITERACY ASSESSMENT TOOL TO SUPPORT HEALTH-CARE PROVIDERS DURING VIRTUAL VISITS","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Health literacy; Diabetes mellitus; Literacy; Pandemic; Health care; Patient education; Health education; Gerontology; Family medicine; Coronavirus disease 2019 (COVID-19); Nursing; Public health; Internal medicine; Disease; Endocrinology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002148138,0.000435517,0.0004628124,0.001155126,0.0003776098,0.001105513,0.0007825941,0.0006225393,0.003573199],"category_scores_gemma":[0.0144726,0.0002786044,0.0006502942,0.0004740014,0.0001187282,0.0009681835,0.0009125055,0.0008626752,0.00099182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005214829,"about_ca_system_score_gemma":0.001951092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002839088,"about_ca_topic_score_gemma":0.004460498,"domain_scores_codex":[0.9987245,0.0005166065,0.0001943303,0.0001244172,0.0002998819,0.0001402792],"domain_scores_gemma":[0.9931411,0.004094687,0.0004924581,0.0001521368,0.001518104,0.0006014689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007465143,0.006397369,0.2105687,0.0009312964,0.0001186569,0.0008679362,0.00419712,0.0008069001,0.006490684,0.0006317389,0.02918871,0.7390543],"study_design_scores_gemma":[0.001281203,0.007430135,0.7714523,0.003877755,0.001311427,0.005354342,0.01900916,0.06072224,0.03740199,0.003274816,0.08830352,0.0005810454],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.917424,0.0009305219,0.04456453,0.004168148,0.0005232169,0.005476879,0.00235832,0.003778542,0.02077588],"genre_scores_gemma":[0.7770853,0.0009084188,0.2060684,0.001541658,0.0001040254,0.004290752,0.002668218,0.0001174894,0.007215679],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.003573199,"threshold_uncertainty_score":0.01195359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0666655892313024,"score_gpt":0.4302775730444254,"score_spread":0.363611983813123,"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."}}