{"id":"W4245756013","doi":"10.1109/acc.2001.946097","title":"An application of discrete-event theory to truck dispatching","year":2001,"lang":"en","type":"article","venue":"","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Truck; Computer science; Context (archaeology); Event (particle physics); Discrete event simulation; Task (project management); Discrete event dynamic system; Context model; Real-time computing; Distributed computing; Discrete system; Engineering; Simulation; Systems engineering; Algorithm; Artificial intelligence; Object (grammar); Automotive engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00194689,0.0007313539,0.0007804322,0.0008734767,0.0009054125,0.002283684,0.002159296,0.001676184,0.005757202],"category_scores_gemma":[0.004828281,0.000609931,0.001555464,0.0008860983,0.002954912,0.003371038,0.001474979,0.002860682,0.0007869202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001507072,"about_ca_system_score_gemma":0.001443985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002846636,"about_ca_topic_score_gemma":0.001811272,"domain_scores_codex":[0.9989237,0.0004169666,0.00006325767,0.0001478745,0.0003675947,0.00008054595],"domain_scores_gemma":[0.9974309,0.001932184,0.00009933071,0.0002587067,0.0001950909,0.00008380453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001329385,0.00002161714,0.0001291482,0.00006356389,0.00001536434,0.0001150667,0.00008264378,0.08437379,0.0002984348,0.9008588,0.0007475068,0.01328076],"study_design_scores_gemma":[0.00001616723,0.00002232451,0.00005305781,0.00004532609,0.000009916499,0.00005232807,0.00004120794,0.3108482,0.0004297325,0.6733382,0.0151274,0.00001610218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002180166,0.0008070274,0.9817956,0.001152877,0.0002476065,0.00002962952,0.00003516285,0.0001044088,0.0136475],"genre_scores_gemma":[0.4481933,0.004590337,0.5344452,0.0008926221,0.0007745951,0.0002749368,0.0001770284,0.0001164764,0.01053554],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005757202,"threshold_uncertainty_score":0.01925981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01266598569991261,"score_gpt":0.2879931324606277,"score_spread":0.2753271467607151,"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."}}