{"id":"W2002238061","doi":"10.3141/2256-10","title":"Future Scenarios for Traffic Information and Management","year":2011,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Regret; Risk analysis (engineering); Transport engineering; Computer science; Process management; Operations research; Business; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.005071339,0.0001728802,0.0002674085,0.0009449702,0.001427713,0.0001595503,0.0006572111,0.000210034,0.0001626802],"category_scores_gemma":[0.00009485397,0.0001405999,0.0002192065,0.001486787,0.0006444519,0.001456574,0.000002808619,0.0008534639,0.000008940593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001384621,"about_ca_system_score_gemma":0.000443355,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004379642,"about_ca_topic_score_gemma":0.04184681,"domain_scores_codex":[0.995002,0.0006831606,0.001055034,0.0002432969,0.00233118,0.0006852808],"domain_scores_gemma":[0.9955441,0.0004021667,0.0004121076,0.0002315683,0.003065819,0.0003442449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.007233817,0.000803269,0.2568559,0.001777379,0.0006471003,0.00009649069,0.3028104,0.009269972,0.0001007282,0.2126324,0.03215319,0.1756194],"study_design_scores_gemma":[0.002008315,0.0004200531,0.759569,0.0002655958,0.00009502754,2.40427e-7,0.03446713,0.0001832729,0.00006248616,0.002576891,0.2001274,0.0002246596],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831795,0.0002541298,0.007021877,0.004683167,0.001077434,0.002415711,0.00009235413,0.00006527767,0.001210518],"genre_scores_gemma":[0.9787428,0.004816364,0.01516586,0.00009420476,0.0002947274,0.0001499547,0.00004799226,0.00003185121,0.0006562308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5027131,"threshold_uncertainty_score":0.9998723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08537183044919099,"score_gpt":0.3709179685180203,"score_spread":0.2855461380688293,"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."}}