{"id":"W1520635673","doi":"10.2196/mhealth.2866","title":"Metadata Correction: Usage of Multilingual Mobile Translation Applications in Clinical Settings","year":2013,"lang":"en","type":"erratum","venue":"JMIR mhealth and uhealth","topic":"Interpreting and Communication in Healthcare","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"mHealth; Computer science; Metadata; World Wide Web; Mobile apps; Internet privacy; Medicine; Nursing; Psychological intervention","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":["metaepi_narrow","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.004345119,0.0004652443,0.001450177,0.0004777073,0.001060332,0.00002322165,0.0006148252,0.001833612,0.0002773119],"category_scores_gemma":[0.0003855397,0.0004415856,0.0001790044,0.0005922245,0.0002527851,0.0002312548,0.0001899418,0.006512436,0.00008465363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004442625,"about_ca_system_score_gemma":0.004393789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00539322,"about_ca_topic_score_gemma":0.001958569,"domain_scores_codex":[0.990202,0.003320105,0.004110586,0.0009081495,0.0004630729,0.0009960621],"domain_scores_gemma":[0.9914781,0.003345052,0.002561619,0.001451703,0.0005792313,0.0005843308],"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":[0.000245155,0.0005361707,0.02357819,0.02283872,0.00004523102,0.000001189191,0.01687568,0.000003874193,9.661993e-7,0.000455366,0.7966381,0.1387813],"study_design_scores_gemma":[0.0013554,0.0004814054,0.02871707,0.003068842,0.0001105198,0.000004121631,0.009948072,0.002324717,7.811182e-7,0.0002437012,0.9533035,0.0004418749],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.2780701,0.1653563,0.002879877,0.01954746,0.1852609,0.08554573,0.005075012,0.002300303,0.2559643],"genre_scores_gemma":[0.494258,0.1127883,0.007554249,0.01253463,0.01202101,0.02953219,0.01486667,0.0006638014,0.3157812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2161878,"threshold_uncertainty_score":0.9998036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1433457086491917,"score_gpt":0.5308237844138306,"score_spread":0.3874780757646389,"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."}}