{"id":"W3001524208","doi":"10.1080/23249935.2020.1720859","title":"System reliability as a surrogate measure of safety for horizontal curves: methodology and case studies","year":2020,"lang":"en","type":"article","venue":"Transportmetrica A Transport Science","topic":"Traffic and Road Safety","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of British Columbia","funders":"","keywords":"Rollover (web design); Reliability (semiconductor); Truck; Monte Carlo method; Mode (computer interface); Modal; Stability (learning theory); Geometric design; Engineering; Reliability engineering; Statistics; Computer science; Transport engineering; Mathematics; Automotive engineering","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":[0.007463939,0.0008714604,0.0006101258,0.002271901,0.0004745984,0.00100782,0.0009705927,0.001187801,0.00151259],"category_scores_gemma":[0.01308087,0.0003515712,0.001012046,0.002183266,0.001327929,0.0006912558,0.0008650112,0.000742342,0.0001522683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001719229,"about_ca_system_score_gemma":0.0009695464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005946107,"about_ca_topic_score_gemma":0.003449976,"domain_scores_codex":[0.9942417,0.00421886,0.0001778733,0.0002834181,0.0008548681,0.000223201],"domain_scores_gemma":[0.9848903,0.01162521,0.001180281,0.001094752,0.001099729,0.0001096808],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0001520675,0.0002796743,0.01375754,0.0001547244,0.00008372126,0.0003308764,0.0002646409,0.9288867,0.002447136,0.02404487,0.0004356717,0.02916232],"study_design_scores_gemma":[0.00002011722,0.0006128171,0.00357501,0.00004026689,0.0000394547,0.0001572283,0.0001628897,0.9862574,0.003642879,0.004478753,0.0009813082,0.00003187929],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5578938,0.0006475155,0.4322974,0.0001375292,0.00002129076,0.0007299147,0.000365775,0.0001702242,0.007736444],"genre_scores_gemma":[0.926591,0.0003337943,0.07175317,0.000009682111,0.00001123941,0.0004341527,0.0001093487,0.00002196472,0.0007356148],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007463939,"threshold_uncertainty_score":0.03947353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06706924376654227,"score_gpt":0.2934466953584852,"score_spread":0.2263774515919429,"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."}}