{"id":"W4405576498","doi":"10.4995/eurocall2024.2024.19054","title":"Exploring potential age, gender, and first language bias when using Google Voice Typing (GVT) for automatic scoring systems in pronunciation placement tests","year":2024,"lang":"en","type":"article","venue":"","topic":"Interpreting and Communication in Healthcare","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université du Québec à Montréal","keywords":"Pronunciation; Dictation; Computer science; Test (biology); Task (project management); Speech recognition; Artificial intelligence; Natural language processing; Psychology; Audiology; Linguistics; Medicine; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.01660769,0.0004966423,0.0003949992,0.001314263,0.0005049529,0.001043735,0.0005059733,0.0003344281,0.001464966],"category_scores_gemma":[0.06333508,0.0002318004,0.0003120388,0.0008605468,0.0006991249,0.0008286845,0.0008512691,0.0002985439,0.0007709824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005366643,"about_ca_system_score_gemma":0.0008342293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008963071,"about_ca_topic_score_gemma":0.02785045,"domain_scores_codex":[0.9868233,0.005903542,0.001557565,0.001223159,0.004031971,0.0004605031],"domain_scores_gemma":[0.9356645,0.03278721,0.01500952,0.003487498,0.012299,0.0007522825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003395256,0.00004951151,0.9398341,0.0001262414,0.00007061016,0.0001609614,0.007874107,0.0002885821,0.005980172,0.0002085942,0.0004142324,0.04465347],"study_design_scores_gemma":[0.00001319566,0.0007406285,0.9823133,0.00008202587,0.0000488366,0.0008008702,0.003683179,0.00190223,0.008042035,0.000294031,0.00201781,0.00006189549],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9915903,0.0002748877,0.005781456,0.0000975439,0.00004281312,0.00008316567,0.0002633328,0.00003667739,0.001829874],"genre_scores_gemma":[0.9930475,0.0001414151,0.005590867,0.0000722746,0.00002082428,0.0000877215,0.0001615679,0.00002608796,0.000851713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01660769,"threshold_uncertainty_score":0.0878309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3991507076407964,"score_gpt":0.4579574123069896,"score_spread":0.0588067046661932,"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."}}