{"id":"W1998907199","doi":"10.1016/j.aap.2012.03.016","title":"Methodology for safety optimization of highway cross-sections for horizontal curves with restricted sight distance","year":2012,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; University of British Columbia","funders":"","keywords":"Reliability (semiconductor); Probabilistic logic; Collision; Sight; Geometric design; Engineering; Reliability engineering; Poison control; Margin (machine learning); Transport engineering; Computer science; Computer security","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001384952,0.001177605,0.001482377,0.001475581,0.0005478833,0.0008951651,0.001579929,0.001320419,0.005356646],"category_scores_gemma":[0.002095517,0.0007533119,0.001849074,0.0009490801,0.0004845606,0.0007043402,0.001097442,0.0009733295,0.0006507195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007838439,"about_ca_system_score_gemma":0.001634728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006053576,"about_ca_topic_score_gemma":0.004021873,"domain_scores_codex":[0.9996186,0.000112186,0.00001769517,0.00007697377,0.0001193324,0.00005520059],"domain_scores_gemma":[0.9991683,0.0004423831,0.00006746951,0.00004442187,0.0002424682,0.00003503127],"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":[0.00002380224,0.00004835688,0.0003366892,0.0001350122,0.00004501721,0.00004135868,0.00004623461,0.9530746,0.00272588,0.005256128,0.0005969598,0.03767005],"study_design_scores_gemma":[0.000004404761,0.00002297621,0.00008200867,0.000009062269,0.000008655066,0.000009658133,0.00001099855,0.9974267,0.0004217745,0.001477821,0.000522097,0.000003944841],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006283207,0.0001414069,0.9916661,0.0000297546,0.00001642475,0.00005978774,0.0000582248,0.0001236896,0.001621256],"genre_scores_gemma":[0.2890451,0.0004800297,0.7040028,0.0000908006,0.00008300773,0.0006533685,0.0004663616,0.0004517102,0.004726804],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006053576,"threshold_uncertainty_score":0.01791972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02937797623579361,"score_gpt":0.3073362960406147,"score_spread":0.2779583198048211,"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."}}