{"id":"W2617620094","doi":"10.1016/j.aap.2017.05.013","title":"A meta-analysis of in-vehicle and nomadic voice-recognition system interaction and driving performance","year":2017,"lang":"en","type":"review","venue":"Accident Analysis & Prevention","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Distraction; Distracted driving; Headway; Phone; Driving simulator; Poison control; Mobile phone; Range (aeronautics); Simulation; Computer science; Engineering; Speech recognition; Telecommunications; Psychology; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001406627,0.0003602906,0.003346336,0.003622152,0.0001735522,0.0001632932,0.0002102006,0.0002800018,0.002319714],"category_scores_gemma":[0.0000427974,0.0003193257,0.002701377,0.001304536,0.00004400724,0.0006511563,0.00008720138,0.000324703,0.0001114474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001630217,"about_ca_system_score_gemma":0.00002535003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003902118,"about_ca_topic_score_gemma":0.005781941,"domain_scores_codex":[0.9962774,0.000876955,0.001702282,0.0006696419,0.000275863,0.0001978948],"domain_scores_gemma":[0.9961753,0.0002598155,0.002691006,0.0006532626,0.0001474642,0.00007319132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.00001605466,0.0001189172,0.01502342,0.0005769721,0.3338994,0.000004620085,0.0005550556,0.00002505418,5.556729e-7,0.0000533106,0.00002085348,0.6497058],"study_design_scores_gemma":[0.0002611708,0.00004751705,0.07988155,0.00102984,0.9018368,0.00001886823,0.00043986,0.003151922,9.18336e-7,0.0000100228,0.01297028,0.0003513152],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.06083489,0.9348029,0.0007020168,0.00001994495,0.0003548536,0.0008600169,0.00000687751,0.00007075975,0.002347673],"genre_scores_gemma":[0.5904974,0.4074777,0.00002982386,0.000004309044,0.00003491273,0.0002166249,0.0004097392,0.00001780683,0.00131168],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.6493545,"threshold_uncertainty_score":0.9999259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2570974739153373,"score_gpt":0.4661791830670513,"score_spread":0.209081709151714,"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."}}