{"id":"W2725076736","doi":"10.2196/diabetes.7446","title":"Machine or Human? Evaluating the Quality of a Language Translation Mobile App for Diabetes Education Material","year":2017,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Interpreting and Communication in Healthcare","field":"Health Professions","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"College of Education and Human Development, Texas A and M University","keywords":"Mobile apps; Computer science; Quality (philosophy); Translation (biology); Machine translation; Diabetes mellitus; Artificial intelligence; World Wide Web; Medicine; Chemistry; Endocrinology; Biochemistry","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":[0.03917013,0.0006579853,0.0007784379,0.001512598,0.0005862891,0.002754544,0.0007274766,0.001155039,0.002586758],"category_scores_gemma":[0.179096,0.0003378055,0.001271658,0.0009809962,0.00120233,0.002475169,0.001364424,0.0006932688,0.0008677155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009726436,"about_ca_system_score_gemma":0.0008761103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001664414,"about_ca_topic_score_gemma":0.002007352,"domain_scores_codex":[0.9723905,0.01382611,0.004548249,0.001998514,0.006746731,0.0004898251],"domain_scores_gemma":[0.7703115,0.1615057,0.01970065,0.008711371,0.03777227,0.001998356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01569274,0.002733654,0.3814338,0.00624098,0.00166226,0.0006787297,0.03014224,0.002893262,0.02203633,0.000733447,0.008525411,0.5272272],"study_design_scores_gemma":[0.001796447,0.03930773,0.786715,0.003623977,0.003642257,0.002353172,0.01963818,0.05400861,0.0564401,0.002155465,0.02965477,0.0006643173],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9788336,0.001303812,0.01215595,0.0006329616,0.0001755481,0.001400775,0.0005111683,0.0004174084,0.004568877],"genre_scores_gemma":[0.9723116,0.0005656035,0.02402969,0.0004390983,0.00007957957,0.0007755248,0.0004936602,0.0001578458,0.001147256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03917013,"threshold_uncertainty_score":0.2071539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1784613869757086,"score_gpt":0.5811876010119537,"score_spread":0.402726214036245,"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."}}