{"id":"W76307491","doi":"","title":"Freight Train Optimization and Simulation","year":2013,"lang":"en","type":"dissertation","venue":"Spectrum Research Repository (Concordia University)","topic":"Simulation Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Train; Freight trains; Rail freight transport; Schedule; Scheduling (production processes); Track (disk drive); Transport engineering; Engineering; Operations research; Passenger train; Computer science; Real-time computing; Automotive engineering; Operations management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00025244,0.0008047497,0.0006122619,0.0004364303,0.0004185004,0.0008488407,0.0008232892,0.00102312,0.01264648],"category_scores_gemma":[0.001189083,0.0002966622,0.0008480072,0.0006596728,0.0004493808,0.0007633847,0.0009343597,0.001010333,0.001172049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001053668,"about_ca_system_score_gemma":0.001021518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02157615,"about_ca_topic_score_gemma":0.01114528,"domain_scores_codex":[0.9997543,0.00006970215,0.00001112571,0.00005550964,0.00004818596,0.00006132368],"domain_scores_gemma":[0.9996506,0.0001925558,0.00004051282,0.00003099567,0.00006047594,0.00002489793],"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":[0.00001091433,0.000008602948,0.0001303328,0.00001658255,0.000005433599,0.00000874929,0.000006033749,0.9919803,0.0001299622,0.003764446,0.0006045087,0.00333416],"study_design_scores_gemma":[0.000002496222,0.000003184057,0.0000358135,0.000002071966,0.000001092081,0.000002316389,0.00000328218,0.9978289,0.00007694616,0.001175318,0.0008672159,0.000001349834],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05692706,0.001243798,0.8480211,0.001163982,0.0002943495,0.0001559413,0.001418851,0.001486515,0.08928836],"genre_scores_gemma":[0.8303207,0.00124577,0.125803,0.0002981704,0.0001166824,0.0003417058,0.00163297,0.0004755104,0.03976553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02157615,"threshold_uncertainty_score":0.04290116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08410688593957494,"score_gpt":0.3812978537765225,"score_spread":0.2971909678369476,"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."}}