{"id":"W3155998765","doi":"10.2196/21586","title":"Designing an App to Overcome Language Barriers in the Delivery of Emergency Medical Services: Participatory Development Process","year":2021,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"Cardiac Arrest and Resuscitation","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bundesamt für Landwirtschaft; Bundesministerium für Ernährung und Landwirtschaft","keywords":"Process (computing); Conversation; Language barrier; USable; Computer science; Participatory design; Health care; Citizen journalism; Medicine; World Wide Web; Psychology; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.001033456,0.00009456123,0.0002419909,0.00008263662,0.0001129695,0.000005576276,0.00006834863,0.00008027977,0.00005951981],"category_scores_gemma":[0.00006909,0.00006812072,0.00002671213,0.0003525377,0.00002056476,0.00006104769,0.00002154869,0.0001880316,0.000003151649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005129922,"about_ca_system_score_gemma":0.001576764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001607078,"about_ca_topic_score_gemma":0.0007139627,"domain_scores_codex":[0.9984081,0.0001888413,0.0004079433,0.0002174123,0.0004686073,0.0003090669],"domain_scores_gemma":[0.9989814,0.00005092875,0.00007541547,0.0001617555,0.00008679845,0.0006436962],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005359891,0.0003881158,0.5950525,0.01193438,0.0000344708,0.0001987465,0.3541283,0.00002226009,0.0006725468,0.0001179391,0.0003700268,0.03654468],"study_design_scores_gemma":[0.001052514,0.0001656722,0.9376828,0.0004592355,0.00004287838,0.00001329837,0.05863586,0.0002214111,0.0004015756,0.00003308256,0.001164458,0.0001271941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964206,0.001458562,0.00005611731,0.001295235,0.0002345789,0.0003859105,0.000003144444,0.00001784722,0.0001280324],"genre_scores_gemma":[0.996156,0.0003055938,0.0003609307,0.002904274,0.0001410289,0.00007905818,0.00003312581,0.000009923014,0.00001004908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3426303,"threshold_uncertainty_score":0.2797111,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0497087579595886,"score_gpt":0.407593755475089,"score_spread":0.3578849975155003,"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."}}