{"id":"W4409700990","doi":"10.3390/smartcities8030073","title":"Intersection Sight Distance in Mixed Automated and Conventional Vehicle Environments with Yield Control on Minor Roads","year":2025,"lang":"en","type":"article","venue":"Smart Cities","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Intersection (aeronautics); Minor (academic); Sight; Yield (engineering); Computer science; Transport engineering; Engineering; Materials science; Physics; Art; Optics; Humanities","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":[0.0011508,0.0005203948,0.0005309317,0.0007365615,0.0005319813,0.001264423,0.001097501,0.0006537205,0.0008601447],"category_scores_gemma":[0.003541474,0.0004479121,0.0005590604,0.0006655104,0.0009660679,0.001403543,0.001323539,0.0003964321,0.0001128101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001465679,"about_ca_system_score_gemma":0.0007837221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01022098,"about_ca_topic_score_gemma":0.007916004,"domain_scores_codex":[0.9985372,0.0004726393,0.00005512426,0.0002415645,0.0002897466,0.0004038136],"domain_scores_gemma":[0.9967135,0.001755099,0.0007094597,0.0002219261,0.0004188032,0.0001812031],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003552659,0.0001267878,0.02359007,0.00002279556,0.00003547308,0.0003480563,0.0001449486,0.9671844,0.002092755,0.002473868,0.00009651884,0.00352911],"study_design_scores_gemma":[0.00001419735,0.0003389637,0.008699788,0.000004353658,0.00002503958,0.0001134339,0.0003252664,0.9870722,0.001692057,0.001508288,0.0001839397,0.00002249552],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9871989,0.00002377749,0.01147079,0.00001794746,0.000003011519,0.00001359923,0.00003890458,0.00002825896,0.001204827],"genre_scores_gemma":[0.9992718,0.000008060748,0.0004878033,0.000001272232,9.052573e-7,0.000004449921,0.00001659319,0.00000274045,0.0002062976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01022098,"threshold_uncertainty_score":0.02032298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004623072204811816,"score_gpt":0.1846447256369882,"score_spread":0.1800216534321764,"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."}}