{"id":"W4293458129","doi":"10.19044/esipreprint.8.2022.p181","title":"A Goal Programming Model for Dispatching Trucks in an Underground Gold Mine","year":2022,"lang":"en","type":"article","venue":"European Scientific Journal ESJ","topic":"Optimization and Mathematical Programming","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Truck; Flexibility (engineering); Underground mining (soft rock); Goal programming; Gold mining; Operations research; Programming paradigm; Engineering; Computer science; Mining engineering; Transport engineering; Coal mining; Waste management; Economics; Automotive engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001277958,0.001044405,0.0007656888,0.0005261279,0.0007882723,0.002024265,0.001304361,0.001652717,0.003056132],"category_scores_gemma":[0.001649047,0.0005758571,0.0008929882,0.001090889,0.0009842864,0.00099009,0.0009054133,0.001437952,0.0003511313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002456555,"about_ca_system_score_gemma":0.003408931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04575798,"about_ca_topic_score_gemma":0.03204642,"domain_scores_codex":[0.9993833,0.0003171962,0.00002341291,0.00009062301,0.00008918298,0.00009612569],"domain_scores_gemma":[0.9991639,0.0005876786,0.00007078843,0.00001579113,0.0001015078,0.00006044015],"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":[0.0000294019,0.00002812493,0.000147928,0.00003679499,0.000009825767,0.00008464458,0.0000509114,0.983182,0.0002462925,0.01408512,0.0002782815,0.001820695],"study_design_scores_gemma":[0.00001688549,0.00002781739,0.00007841337,0.000008210384,0.000006481812,0.00001034939,0.00004496708,0.9945939,0.00008331964,0.004564177,0.000559547,0.000005935805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09541953,0.0004057291,0.8697138,0.001179472,0.00008116833,0.0002373563,0.0006926051,0.0002519438,0.03201842],"genre_scores_gemma":[0.8287655,0.0007994057,0.1527366,0.0001829477,0.00004045024,0.0005977692,0.000440572,0.00005940138,0.01637746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04575798,"threshold_uncertainty_score":0.09098327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0310343565394639,"score_gpt":0.2600064596675246,"score_spread":0.2289721031280607,"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."}}