{"id":"W4391546781","doi":"10.1007/978-3-031-34027-7_37","title":"Improving Safety of Rural Intersection with Approaching Reverse Curve","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in civil engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Regional Municipality of Niagara; Toronto Metropolitan University","funders":"","keywords":"Intersection (aeronautics); Computer science; Geography; Cartography","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":[0.0003512579,0.0007438003,0.0005703907,0.0006038949,0.0006907594,0.0006924919,0.001330127,0.0006439427,0.007632419],"category_scores_gemma":[0.0009800363,0.0001938319,0.0005077038,0.0005590647,0.0003961257,0.000838513,0.001313551,0.0008237475,0.001460418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004825067,"about_ca_system_score_gemma":0.0009900923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004903625,"about_ca_topic_score_gemma":0.003996516,"domain_scores_codex":[0.9996036,0.00007636238,0.000008353826,0.00006391107,0.0001609393,0.00008681169],"domain_scores_gemma":[0.9996504,0.00009560677,0.00004055162,0.00004665745,0.0001352752,0.00003164947],"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":[0.0006193932,0.0003302777,0.007422879,0.0003053644,0.0000663585,0.0004678842,0.0004409428,0.4943995,0.03963916,0.01679907,0.008827657,0.4306815],"study_design_scores_gemma":[0.00004953488,0.002250598,0.01088546,0.0000909467,0.0001448788,0.0008648006,0.001220539,0.8890367,0.03495107,0.02616056,0.03428087,0.00006404369],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3998915,0.001845296,0.5037588,0.0007348765,0.0002513603,0.0001593796,0.0003681248,0.002143707,0.09084703],"genre_scores_gemma":[0.9350878,0.0007523238,0.03593707,0.0000667155,0.00006087888,0.00003549199,0.000481982,0.0001354509,0.02744232],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007632419,"threshold_uncertainty_score":0.02553296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003822169662128362,"score_gpt":0.1725008321591975,"score_spread":0.1686786624970691,"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."}}