{"id":"W1973297206","doi":"10.1007/s10100-007-0037-8","title":"An application of discrete-event theory to truck dispatching","year":2007,"lang":"en","type":"article","venue":"Central European Journal of Operations Research","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Syncrude","keywords":"Truck; Computer science; Discrete event simulation; Theory of constraints; Formalism (music); Process (computing); Operations research; Event (particle physics); Task (project management); Range (aeronautics); Industrial engineering; Simulation; Systems engineering; Operations management; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01392531,0.0000888634,0.0001559591,0.0004739664,0.0002549177,0.000231548,0.001661104,0.00001794886,0.0000076448],"category_scores_gemma":[0.0003473137,0.00007235162,0.0000701404,0.0007905012,0.00005983458,0.00071624,0.00021119,0.0003784052,0.00002248822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001365999,"about_ca_system_score_gemma":0.0001522333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001289308,"about_ca_topic_score_gemma":0.00001595698,"domain_scores_codex":[0.9961395,0.001510556,0.0007756122,0.0002237743,0.0009138869,0.0004367279],"domain_scores_gemma":[0.9979932,0.0001691312,0.00009844988,0.0005689298,0.0007875719,0.0003827707],"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":[0.0001352665,0.0003408967,0.00137948,0.00003038964,0.000043266,0.0001380487,0.01096131,0.4096224,0.1160788,0.1203865,0.0001825678,0.340701],"study_design_scores_gemma":[0.001919923,0.002795795,0.08887098,0.0006141755,0.00002383386,0.000507061,0.003739716,0.853655,0.03737174,0.001827425,0.007958231,0.0007160968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2419602,0.00007908321,0.7566534,0.0002739821,0.0001477549,0.0001584305,0.000001787667,0.00001009992,0.0007152958],"genre_scores_gemma":[0.9283224,0.0000134252,0.07129799,0.00003502821,0.0002623254,0.000001128084,0.000001378867,0.00001457091,0.00005179225],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6863622,"threshold_uncertainty_score":0.4826262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04644632984681485,"score_gpt":0.3836589797095322,"score_spread":0.3372126498627174,"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."}}