{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001215423,0.0005039172,0.00029751,0.0003180296,0.0002759892,0.0005846454,0.0002678192,0.0004339571,0.001778229],"category_scores_gemma":[0.0146322,0.0001690982,0.0003169626,0.0001306997,0.0003476929,0.0003882824,0.0005403148,0.0002642699,0.000300384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002062464,"about_ca_system_score_gemma":0.0001908188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007837856,"about_ca_topic_score_gemma":0.0009165472,"domain_scores_codex":[0.9988139,0.0004003957,0.0001276557,0.0001581851,0.0003711482,0.0001288488],"domain_scores_gemma":[0.9906245,0.006241336,0.001084977,0.0004736235,0.001108475,0.0004670448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.02124216,0.003697535,0.3468976,0.0009343421,0.0002905048,0.001029913,0.005740482,0.001923352,0.3734219,0.0001217768,0.0004127804,0.2442875],"study_design_scores_gemma":[0.0001870489,0.02799193,0.8737578,0.0000539752,0.0002886425,0.001643135,0.001548311,0.002795895,0.09053347,0.0001576592,0.000984501,0.00005762427],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986688,0.00007535291,0.0009192922,0.00001229827,0.000007827521,0.000015017,0.00002225905,0.0000111887,0.0002680118],"genre_scores_gemma":[0.9985746,0.00005984756,0.0009697007,0.000026041,0.00001288798,0.00002545273,0.00007129354,0.000008322671,0.0002518521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001778229,"threshold_uncertainty_score":0.006427884,"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."}}