{"id":"W175365921","doi":"","title":"In-Vehicle Intelligent Transportation System (ITS) Countermeasures to Improve Older Driver Intersection Performance","year":2006,"lang":"en","type":"article","venue":"","topic":"Older Adults Driving Studies","field":"Health Professions","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Intersection (aeronautics); Clearance; Advanced driver assistance systems; Intelligent transportation system; Transport engineering; Driving simulator; Computer science; Measure (data warehouse); Simulation; Engineering; Artificial intelligence; Medicine; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000342859,0.0001757093,0.0002314163,0.0001835574,0.0003092522,0.00001066824,0.0001181266,0.0001123065,0.0001769841],"category_scores_gemma":[0.0000193181,0.0001500694,0.00004717257,0.0002457529,0.00002114804,0.0002937782,0.00002404789,0.0003013079,0.0007374533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006118712,"about_ca_system_score_gemma":0.00005071816,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002155122,"about_ca_topic_score_gemma":0.02278048,"domain_scores_codex":[0.9982537,0.00009805357,0.0006187148,0.0003350398,0.0002583741,0.0004361404],"domain_scores_gemma":[0.9993073,0.00008584998,0.0001156629,0.0001899621,0.0002434978,0.00005777365],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006851892,0.0001331839,0.9577483,0.001405997,0.00003035786,0.00000729361,0.01597983,0.0006927187,0.007531927,0.001155372,0.01408234,0.001164158],"study_design_scores_gemma":[0.0006377635,0.00008825403,0.9823706,0.0008548219,0.00001580198,5.308278e-7,0.007673283,0.002238113,0.003684685,0.00001139527,0.002221701,0.0002030721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9880146,0.00002634644,0.002078843,0.0004893605,0.001657428,0.001130217,0.00001136269,0.0002043804,0.006387461],"genre_scores_gemma":[0.9920529,0.00001005969,0.00006611884,0.000434672,0.0002713968,0.000294651,0.000007326943,0.00002607983,0.006836815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02462228,"threshold_uncertainty_score":0.9950512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0183739670799659,"score_gpt":0.3233571403429894,"score_spread":0.3049831732630235,"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."}}