{"id":"W2626613082","doi":"","title":"Locomotive assignment under consist busting and maintenance constraints","year":2014,"lang":"en","type":"article","venue":"Les Cahiers du GERAD","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Pacific Railway (Canada); Concordia University","funders":"","keywords":"Column generation; Train; Heuristics; Scalability; Decomposition; String (physics); Optimization problem; Computer science; Engineering; Mathematical optimization; Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002008572,0.0001510865,0.000177759,0.00004412788,0.0001447688,0.00004620478,0.00007142733,0.00009540338,0.00002554127],"category_scores_gemma":[0.00004427598,0.0001383069,0.00003209989,0.00007210644,0.0003329852,0.00005032753,0.00001334464,0.0001582208,0.00001295983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009448468,"about_ca_system_score_gemma":0.000008071263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003334271,"about_ca_topic_score_gemma":0.00001239589,"domain_scores_codex":[0.999228,0.00003342439,0.0001789948,0.0001795824,0.0001080306,0.0002719867],"domain_scores_gemma":[0.999609,0.0001051281,0.00003308155,0.0001316183,0.00002493944,0.00009624461],"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":[0.00001342847,0.00006705194,0.005463,0.0003588133,0.0002539669,0.0000639739,0.004991503,0.1768464,0.01217745,0.6778083,0.0059847,0.1159713],"study_design_scores_gemma":[0.008288979,0.0005479906,0.07103459,0.001304507,0.0002117554,0.001075258,0.01835777,0.6954418,0.01088853,0.02228894,0.1656938,0.00486605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.617927,0.000253405,0.3361178,0.0002147753,0.0005298979,0.0001223304,0.000006093726,0.0002564222,0.04457232],"genre_scores_gemma":[0.9976144,0.00002808466,0.001738298,0.0001270954,0.0001041789,0.000009939942,0.000002325022,0.00002291974,0.0003527383],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6555194,"threshold_uncertainty_score":0.563999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004225027175911758,"score_gpt":0.1605987540331355,"score_spread":0.1563737268572238,"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."}}