{"id":"W581241149","doi":"","title":"An Approach to Incorporate Uncertainty and Risk in Transportation Investment Decision Making: Detroit River International Crossing Case Study","year":2011,"lang":"en","type":"article","venue":"Transportation Research Board 90th Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Investment (military); Risk analysis (engineering); Option value; Economics; Policy analysis; Business; Actuarial science; Operations research; Engineering; Microeconomics; Incentive","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.01298257,0.0005371032,0.0006138212,0.003023908,0.002978166,0.0006182901,0.0009009,0.0004527456,0.0001978771],"category_scores_gemma":[0.0006928456,0.000591583,0.0001433576,0.00411264,0.0015569,0.002244458,0.00001105419,0.001744394,0.00002712166],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005118817,"about_ca_system_score_gemma":0.001095524,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2035372,"about_ca_topic_score_gemma":0.3981931,"domain_scores_codex":[0.9873614,0.002821716,0.001815645,0.001871681,0.004441875,0.001687733],"domain_scores_gemma":[0.993098,0.0009450137,0.0004126201,0.000632623,0.003524341,0.001387359],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0013505,0.001412092,0.6050431,0.0000554079,0.00006602565,0.0009916413,0.3603444,0.02152554,0.0000284938,0.003182234,0.0001256432,0.005874951],"study_design_scores_gemma":[0.002090444,0.0007265796,0.7759145,0.0001864553,0.00006005618,0.000002371808,0.215798,0.001513187,0.00002308217,0.002049048,0.00109426,0.0005420286],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842281,0.00005785643,0.00890338,0.0001473292,0.0002637677,0.003675226,0.0005550483,0.0002868602,0.001882401],"genre_scores_gemma":[0.9644384,0.000214427,0.03359441,0.0001029705,0.0001514404,0.0007457339,0.000521476,0.0001018764,0.0001292455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.194656,"threshold_uncertainty_score":0.9996536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1008482036616623,"score_gpt":0.414764239161091,"score_spread":0.3139160354994286,"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."}}