{"id":"W2034644212","doi":"10.1016/j.ijhcs.2006.07.006","title":"Do in-vehicle advanced signs enhance older and younger drivers’ intersection performance? Driving simulation and eye movement results","year":2007,"lang":"en","type":"article","venue":"International Journal of Human-Computer Studies","topic":"Older Adults Driving Studies","field":"Health Professions","cited_by":97,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Government of Canada; Transport Canada","keywords":"Intersection (aeronautics); Driving simulator; Eye movement; Perception; Psychology; Driving simulation; Audiology; Simulation; Physical medicine and rehabilitation; Computer science; Transport engineering; Medicine; Engineering; Artificial intelligence","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":[0.001095574,0.0001922777,0.0003446729,0.0004248539,0.0003813528,0.00003164612,0.0001692337,0.00006518373,0.000007999339],"category_scores_gemma":[0.0001504326,0.0001642735,0.00004998182,0.00009549284,0.0001119808,0.0007145669,0.0003632906,0.0004434683,0.000003348705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004367946,"about_ca_system_score_gemma":0.00002236411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001912443,"about_ca_topic_score_gemma":0.0004529124,"domain_scores_codex":[0.9978766,0.00009439801,0.001022144,0.0002670983,0.0004492792,0.0002904764],"domain_scores_gemma":[0.9976225,0.0006623524,0.0006736428,0.0000967424,0.0008865932,0.00005818136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003091581,0.000181128,0.8323119,0.0001579627,0.000813987,0.00007871985,0.1057322,0.003873397,0.003486345,0.0001677161,0.0007153812,0.05217213],"study_design_scores_gemma":[0.002959826,0.0004298196,0.9833167,0.00209077,0.0000262311,0.000004695198,0.007720585,0.002156933,0.0003370678,0.0003231464,0.0004430661,0.0001911174],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991069,0.0006088161,0.004615962,0.0007094222,0.002491371,0.0002375477,0.000002192446,0.00002216312,0.0002435],"genre_scores_gemma":[0.9969424,0.0006235105,0.001050806,0.0003346301,0.0008233967,0.00000614036,0.000001244969,0.0000148158,0.0002030838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1510048,"threshold_uncertainty_score":0.6698878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04378612442735819,"score_gpt":0.4470710262479844,"score_spread":0.4032849018206262,"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."}}