{"id":"W2032349706","doi":"10.1518/0018720054679515","title":"Effects of Voice Technology on Test Track Driving Performance: Implications for Driver Distraction","year":2005,"lang":"en","type":"article","venue":"Human Factors The Journal of the Human Factors and Ergonomics Society","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":131,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"Transport Canada; U.S. Department of Transportation","keywords":"Distraction; Task (project management); Interface (matter); Phone; Driving simulator; Computer science; Track (disk drive); Cognition; Human–computer interaction; Simulation; Engineering; Psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003637367,0.0002404443,0.0003308395,0.0001089523,0.001114149,0.00004455146,0.0004768612,0.0002016913,0.000109396],"category_scores_gemma":[0.00007006971,0.0001433114,0.0004400726,0.0001124198,0.0002790119,0.0002373801,0.00005568141,0.0006007036,0.000005776893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002226629,"about_ca_system_score_gemma":0.00002851808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001220058,"about_ca_topic_score_gemma":0.00002985079,"domain_scores_codex":[0.9986842,0.0000772238,0.0006964942,0.0001719785,0.0001239447,0.0002461094],"domain_scores_gemma":[0.9974373,0.0008592741,0.001114186,0.0003587672,0.0001574976,0.00007295241],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000193817,0.001803993,0.7503681,0.0002093077,0.001188324,1.876706e-7,0.04377199,0.0008463607,0.1578943,0.01334834,0.02721941,0.003155888],"study_design_scores_gemma":[0.0008051305,0.0003186132,0.9817665,0.00005953168,0.0001573574,0.00001122598,0.00197465,0.00006065772,0.008124815,0.0002785999,0.006284909,0.0001580506],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981382,0.00004604586,0.0001876509,0.0004573614,0.0005659285,0.0003404136,0.0000242824,0.00003067667,0.0002094045],"genre_scores_gemma":[0.9988075,0.00006257635,0.00003848593,0.0001027878,0.0002464015,0.000009543465,0.00000640427,0.00002859156,0.0006977263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2313984,"threshold_uncertainty_score":0.8569249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02277300555706485,"score_gpt":0.3140733631821755,"score_spread":0.2913003576251107,"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."}}