{"id":"W2735702858","doi":"10.1007/s11081-017-9361-6","title":"A stochastic optimization formulation for the transition from open pit to underground mining","year":2017,"lang":"en","type":"article","venue":"Optimization and Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Group for Research in Decision Analysis; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; AngloGold Ashanti; Newmont Corporation; Barrick Gold Corporation","keywords":"Open-pit mining; Cash flow; Net present value; Computer science; Financial engineering; Set (abstract data type); Mathematical optimization; Production (economics); Mining engineering; Present value; Underground mining (soft rock); Operations research; Geology; Mathematics; Engineering; Economics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001694799,0.001132487,0.001138631,0.00063864,0.0005023415,0.001741083,0.001311218,0.001576149,0.005448784],"category_scores_gemma":[0.002275966,0.0008655706,0.00110949,0.0009117394,0.000947657,0.001189445,0.0009264364,0.001829857,0.0003375454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002169203,"about_ca_system_score_gemma":0.003360775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01136948,"about_ca_topic_score_gemma":0.008910882,"domain_scores_codex":[0.9992296,0.0002978971,0.00002886295,0.0001524942,0.0001603359,0.0001308891],"domain_scores_gemma":[0.9990101,0.0006131168,0.0001517456,0.00002767145,0.0001222299,0.00007514934],"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":[0.00001561842,0.00001611417,0.0001506536,0.00002714718,0.00001095944,0.00003543433,0.00001210046,0.9848205,0.0002207557,0.01282876,0.0002915554,0.001570259],"study_design_scores_gemma":[0.000007864279,0.00002355746,0.0001200892,0.000007206291,0.000007874523,0.000009306416,0.00001234487,0.9932622,0.00009607508,0.006002303,0.0004455329,0.000005614433],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0332716,0.0004393091,0.9500774,0.0009325055,0.00008930683,0.0001187656,0.0005690222,0.0001035769,0.01439869],"genre_scores_gemma":[0.8328389,0.0009016967,0.1467023,0.0002142846,0.0001079286,0.0004821213,0.0005307021,0.0001064323,0.01811563],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01136948,"threshold_uncertainty_score":0.02260655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02405759604799163,"score_gpt":0.236973812695526,"score_spread":0.2129162166475344,"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."}}