{"id":"W2597846560","doi":"10.1057/s41274-017-0201-z","title":"Dig-limits optimization through mixed-integer linear programming in open-pit mines","year":2017,"lang":"en","type":"article","venue":"Journal of the Operational Research Society","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Loader; Excavator; Open-pit mining; Integer programming; Linear programming; Engineering; Computer science; Mining engineering; Civil engineering; Mathematical optimization; Mathematics; Mechanical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002001141,0.00008186369,0.0001519289,0.00002835326,0.0004702372,0.000609847,0.00110896,0.00008507325,0.0000463031],"category_scores_gemma":[0.0004853031,0.00005817902,0.0001234324,0.00008425787,0.00009484149,0.0009667745,0.0002779956,0.0004774297,0.000002884994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002269792,"about_ca_system_score_gemma":0.0001404938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004122402,"about_ca_topic_score_gemma":0.00004616002,"domain_scores_codex":[0.9989941,0.00005168402,0.0003282764,0.00009209976,0.0003160897,0.0002177926],"domain_scores_gemma":[0.9991609,0.00009569651,0.00009880542,0.0002790402,0.0003195431,0.0000459826],"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":[0.00003157684,0.00009593883,0.003291728,0.0000456064,0.00009463407,0.000005195684,0.001557725,0.9153793,0.0008480765,0.002567413,0.07378188,0.002300969],"study_design_scores_gemma":[0.0007866651,0.0001018444,0.002037542,0.0003071882,0.000008097247,0.00003345646,0.0005787651,0.9392061,0.00388027,0.001189251,0.05168625,0.0001846047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8235932,0.0009074155,0.128727,0.02580475,0.002365686,0.002074824,0.00003600117,0.00009284156,0.01639832],"genre_scores_gemma":[0.8066642,0.0009761965,0.1907047,0.00009949354,0.0005657303,0.00002884946,0.000004191788,0.00003453513,0.0009220393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06197773,"threshold_uncertainty_score":0.5880768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.133189246430766,"score_gpt":0.4041430888361794,"score_spread":0.2709538424054134,"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."}}