{"id":"W1171884358","doi":"10.1016/j.aap.2015.08.005","title":"Transferability of calibrated microsimulation model parameters for safety assessment using simulated conflicts","year":2015,"lang":"en","type":"article","venue":"Accident Analysis & Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":93,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"VisSim; Microsimulation; Intersection (aeronautics); Calibration; Traffic simulation; Transferability; Field (mathematics); Traffic conflict; Computer science; Simulation; Poison control; Correlation; Transport engineering; Engineering; Statistics; Traffic congestion; Mathematics; Machine learning","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":[0.001573459,0.0006305132,0.0003854769,0.0005441695,0.0003121837,0.0006320703,0.0007267358,0.0009932029,0.001926856],"category_scores_gemma":[0.01471806,0.0003267088,0.0004336954,0.0003499328,0.0004377795,0.001127326,0.0006375129,0.0009364773,0.0001894562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007917073,"about_ca_system_score_gemma":0.000977275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007777982,"about_ca_topic_score_gemma":0.002356025,"domain_scores_codex":[0.9995294,0.0002214021,0.00002221573,0.00007311434,0.00008296611,0.00007104716],"domain_scores_gemma":[0.9948472,0.003511796,0.0003537925,0.0006646874,0.0005470949,0.00007551238],"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":[0.00004841829,0.00003222761,0.0007982278,0.00001108503,0.00001003574,0.00001238706,0.00002174905,0.9946764,0.0007618251,0.0007333173,0.00005702191,0.002837265],"study_design_scores_gemma":[0.00001031542,0.00003250179,0.0004996495,0.000005041574,0.000004816285,0.000005116617,0.00001406433,0.9975728,0.001039666,0.0007538096,0.00005662167,0.000005520487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7443093,0.0000768528,0.2488771,0.0002218486,0.00005548576,0.000112388,0.0002891195,0.0007286842,0.005329219],"genre_scores_gemma":[0.9961613,0.000009818357,0.003594744,0.00001017561,0.000001611947,0.00002837944,0.00005847373,0.00002482192,0.0001105023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007777982,"threshold_uncertainty_score":0.01546544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06765022290998338,"score_gpt":0.3320442344680164,"score_spread":0.264394011558033,"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."}}