{"id":"W1522016728","doi":"10.18757/ejtir.2003.3.1.4234","title":"Decision Support in Dynamic Traffic Management","year":2003,"lang":"en","type":"article","venue":"European journal of transport and infrastructure research","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Transportation of Ontario","funders":"","keywords":"Computer science; Operator (biology); Set (abstract data type); Fuel efficiency; Task (project management); Function (biology); Decision support system; Operations research; Control (management); Similarity (geometry); Fuzzy logic; Data mining; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00267523,0.000767654,0.0008250653,0.001210526,0.0008574091,0.004361121,0.001133727,0.001342274,0.0045619],"category_scores_gemma":[0.00725823,0.000269655,0.0003992175,0.001468073,0.0009715299,0.002328699,0.001853006,0.001243664,0.0007872614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118109,"about_ca_system_score_gemma":0.001423319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005072846,"about_ca_topic_score_gemma":0.002458633,"domain_scores_codex":[0.9981557,0.0008295045,0.0001757651,0.0003118,0.0003983243,0.0001289132],"domain_scores_gemma":[0.996487,0.002568277,0.0002378262,0.0001611152,0.0003876337,0.0001581983],"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":[0.0003269386,0.0002497243,0.00207918,0.0004518035,0.0001077018,0.0007044466,0.0004773175,0.4944479,0.002264615,0.1794145,0.009688461,0.3097875],"study_design_scores_gemma":[0.00005785897,0.00007623827,0.0003694331,0.0000860918,0.00002236422,0.00008379534,0.000191151,0.8579069,0.0009371621,0.1253023,0.01494272,0.00002400019],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05309558,0.003913395,0.8966359,0.005571709,0.0005185626,0.0002694805,0.0005956706,0.001756825,0.03764289],"genre_scores_gemma":[0.8545659,0.002067018,0.1369716,0.0003576084,0.0003092907,0.0002177927,0.0005518498,0.00005262246,0.004906446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005072846,"threshold_uncertainty_score":0.01526105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01732469915523118,"score_gpt":0.2860057976596367,"score_spread":0.2686810985044055,"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."}}