{"id":"W4400083320","doi":"10.1007/s42461-024-01005-2","title":"Stochastic Optimization for Long-Term Planning of a Mining Complex with In-Pit Crushing and Conveying Systems","year":2024,"lang":"en","type":"article","venue":"Mining Metallurgy & Exploration","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Crusher; Haulage; Open-pit mining; Schedule; Simulated annealing; Production schedule; Truck; Computer science; Flexibility (engineering); Metaheuristic; Engineering; Operations research; Mining engineering; Scheduling (production processes); Automotive engineering; Operations management; Mechanical engineering; Rope; Algorithm","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001880202,0.0009635,0.001247709,0.0007347244,0.0006508122,0.00121757,0.00102218,0.001466314,0.002890735],"category_scores_gemma":[0.003198394,0.001137543,0.001065875,0.0008474971,0.001096165,0.0006827521,0.0008866582,0.001320482,0.00021292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002298041,"about_ca_system_score_gemma":0.002136358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03129549,"about_ca_topic_score_gemma":0.02087089,"domain_scores_codex":[0.9993445,0.000310968,0.00002444905,0.00009544453,0.0001117329,0.0001129099],"domain_scores_gemma":[0.9977442,0.001604769,0.0002340605,0.00005071465,0.0002422515,0.0001240273],"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":[0.000005883343,0.00000337205,0.00004928187,0.000003135181,0.000003046451,0.000007750386,0.000002946882,0.9990327,0.00004993007,0.0005168783,0.00002248272,0.000302568],"study_design_scores_gemma":[0.000002776238,0.000008097947,0.00004652041,0.000001161343,0.000001861192,9.700078e-7,0.000003504026,0.9994813,0.00003064314,0.0003801659,0.00004154693,0.000001460039],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1811667,0.0003122237,0.8075187,0.0006026326,0.00005915408,0.0001582422,0.0004150347,0.0002568052,0.009510594],"genre_scores_gemma":[0.9501354,0.0001292892,0.04577696,0.00004824823,0.00001607657,0.0001894582,0.0001901752,0.00005039896,0.003464145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03129549,"threshold_uncertainty_score":0.06222665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06713555786053445,"score_gpt":0.2662474042846716,"score_spread":0.1991118464241372,"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."}}