{"id":"W2055921086","doi":"10.3141/1862-15","title":"Risk-Based Model for Identifying Highway-Rail Grade Crossing Blackspots","year":2004,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Collision; Negative binomial distribution; Computer science; Level crossing; Poisson distribution; Poison control; Simulation; Transport engineering; Statistics; Geography; Engineering; Mathematics; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002357294,0.001095908,0.001099056,0.001556794,0.0006934478,0.001836149,0.002942956,0.001510588,0.006954444],"category_scores_gemma":[0.004712821,0.0006518932,0.001114124,0.001003844,0.0008156379,0.001362736,0.0009899221,0.001549566,0.00119227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00367741,"about_ca_system_score_gemma":0.002705542,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08695837,"about_ca_topic_score_gemma":0.04266446,"domain_scores_codex":[0.9989786,0.0002126829,0.00005991319,0.0002872091,0.0002614473,0.00020027],"domain_scores_gemma":[0.9981356,0.0009056304,0.0002931451,0.00005348935,0.0005091177,0.0001029098],"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":[0.00005751511,0.00003167973,0.00423486,0.00002479372,0.0000337934,0.0001261558,0.00007888487,0.9809849,0.0002579448,0.007911655,0.0008008802,0.005456916],"study_design_scores_gemma":[0.000009037963,0.00001905906,0.0008237376,0.000006662155,0.00001630472,0.00003046882,0.00002099392,0.9960822,0.0000540312,0.002615573,0.0003110556,0.00001087804],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1927176,0.000438872,0.787379,0.001405032,0.0001247087,0.0003640362,0.00280458,0.001140085,0.01362604],"genre_scores_gemma":[0.9486121,0.0003441542,0.03268046,0.00009928823,0.00005338238,0.0003965262,0.001359729,0.0000740652,0.01638023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08695837,"threshold_uncertainty_score":0.1729044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1107632981290078,"score_gpt":0.3761903370538997,"score_spread":0.2654270389248919,"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."}}