{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003018366,0.0001166688,0.0002543668,0.00003988273,0.002140946,0.00003588982,0.0005402452,0.0001303649,0.0002959097],"category_scores_gemma":[0.0009217487,0.00007770841,0.00008190632,0.00003923625,0.00009808959,0.0001116238,0.00008899432,0.0002411316,0.00001116411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000503297,"about_ca_system_score_gemma":0.0002147407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003246695,"about_ca_topic_score_gemma":0.0001517266,"domain_scores_codex":[0.9974967,0.001190973,0.0006696259,0.0001748407,0.0001756686,0.0002922042],"domain_scores_gemma":[0.9958986,0.001877734,0.0008515484,0.001041387,0.000291122,0.00003959165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006816176,0.0005007891,0.4780662,0.008313263,0.0001177449,3.132952e-8,0.07532113,0.00001002713,0.1523719,0.004249488,0.002193006,0.2781748],"study_design_scores_gemma":[0.006424966,0.004616204,0.7965331,0.009007429,0.0003447276,2.427564e-7,0.06412015,0.02478217,0.05398811,0.01691036,0.02146333,0.001809199],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935655,0.0003418475,0.000008123324,0.00114558,0.0005730789,0.002471866,0.0001843833,0.00006730909,0.001642343],"genre_scores_gemma":[0.9909955,0.000005688038,0.0006699163,0.0003671724,0.0003660678,0.006501118,0.0001836442,0.00002434195,0.0008865393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3184669,"threshold_uncertainty_score":0.9991581,"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."}}