{"id":"W2380700878","doi":"10.1139/cjce-2015-0478","title":"Safety evaluation of unconventional outside left-turn lane using automated traffic conflict techniques","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Traffic and Road Safety","field":"Engineering","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Fundamental Research Funds for the Central Universities; Graduate Research and Innovation Projects of Jiangsu Province; Government of Jiangsu Province; Southeast University; National Natural Science Foundation of China","keywords":"Intersection (aeronautics); Traffic conflict; Left behind; Collision; Transport engineering; Turn (biochemistry); Left and right; Computer science; Simulation; Engineering; Computer security; Traffic congestion; Psychology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0007760699,0.0001651942,0.000281147,0.0004400852,0.00003845522,0.00001392686,0.0001596591,0.0001167077,0.0003051504],"category_scores_gemma":[0.0001001157,0.0001365204,0.0001251585,0.0001468841,0.00003631772,0.0001994645,0.000004661855,0.0001614616,0.000002813244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005144481,"about_ca_system_score_gemma":0.0005504545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007633708,"about_ca_topic_score_gemma":0.007737932,"domain_scores_codex":[0.9987228,0.00003037885,0.0005605876,0.00008379359,0.0003161132,0.0002863162],"domain_scores_gemma":[0.9991093,0.00005795883,0.0001194303,0.0001232744,0.0002878515,0.0003021339],"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":[0.000005914843,0.000004806257,0.0003811468,0.00005846244,0.000136502,0.00002003857,0.0001989696,0.9804538,0.009615226,0.0001154486,0.0006126544,0.008396965],"study_design_scores_gemma":[0.001889998,0.00009588742,0.0257255,0.00178881,0.0002776739,0.0007071596,0.00007777735,0.9434631,0.008105106,0.00004481253,0.01721931,0.0006048537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8967139,0.003536166,0.09343141,0.0001897894,0.002289081,0.0003704262,0.0001518328,0.00064556,0.002671841],"genre_scores_gemma":[0.9986408,0.00004531367,0.001089599,0.000004922874,0.0001607738,9.524686e-7,0.000003498578,0.00003957452,0.00001458372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1019269,"threshold_uncertainty_score":0.556714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01825110029581845,"score_gpt":0.230576555984467,"score_spread":0.2123254556886486,"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."}}