{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004198576,0.00008131404,0.00009036915,0.00006674114,0.00004506571,0.00001719021,0.00003210655,0.00003842416,0.00004179731],"category_scores_gemma":[0.000003876497,0.00007088012,0.00001243617,0.00006679824,0.00004118056,0.00007542554,0.000007109443,0.00008718031,0.000005768393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005422901,"about_ca_system_score_gemma":0.000006393843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001916754,"about_ca_topic_score_gemma":0.00009581417,"domain_scores_codex":[0.9996244,0.000009834986,0.0001028097,0.00009163635,0.00006294909,0.0001083248],"domain_scores_gemma":[0.9998575,0.00003803609,0.00001147842,0.0000675291,0.000003815584,0.00002159976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008185233,0.0001855193,0.8922237,0.0004911579,0.0002618273,0.00002927233,0.001375034,0.05247217,0.03018657,0.003071196,0.00871045,0.01017457],"study_design_scores_gemma":[0.001674929,0.0001110588,0.6788095,0.0004667409,0.0000120511,0.000002680624,0.00032993,0.2973788,0.007352721,0.0000832075,0.01358529,0.0001930342],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951971,0.0001627445,0.001261293,0.00008629406,0.0001951597,0.00008669539,0.00001135677,0.0001047945,0.002894518],"genre_scores_gemma":[0.9983794,0.00002388286,0.00002592605,0.00005258262,0.00001451645,0.00002637789,0.000006017839,0.00000674343,0.00146454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2449067,"threshold_uncertainty_score":0.2890407,"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."}}