{"id":"W2976804862","doi":"10.22044/jme.2019.7333.1582","title":"Application of Sequential Gaussian Conditional Simulation to Underground Mine Design Under Grade Uncertainty","year":2020,"lang":"en","type":"article","venue":"Journal of mining and environment","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Kriging; Range (aeronautics); Gaussian; Heuristic; Computer science; Geostatistics; Data mining; Mining engineering; Mathematical optimization; Engineering; Spatial variability; Statistics; Mathematics; Machine learning; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000130208,0.00006907128,0.000129831,0.0000374558,0.00002050379,0.000009087797,0.00004821376,0.00003831046,0.00002980628],"category_scores_gemma":[0.000006079369,0.00006846103,0.00002992292,0.00002359082,0.000017884,0.00005407961,0.00001401601,0.00005353333,0.000001958668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007210012,"about_ca_system_score_gemma":0.000006831366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001846321,"about_ca_topic_score_gemma":4.006067e-7,"domain_scores_codex":[0.999499,0.00001196607,0.0002678421,0.00006609991,0.00008405137,0.00007106627],"domain_scores_gemma":[0.9997109,0.00004908913,0.0000982495,0.00004643271,0.000005148921,0.000090177],"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":[0.00002186699,0.00001051796,0.0001887073,0.00001290684,0.00002936768,9.515368e-7,0.0003796908,0.9907271,0.00597318,0.00007813864,0.0003489007,0.00222871],"study_design_scores_gemma":[0.0003824752,0.0003307676,0.002641908,0.00002471367,0.00003966369,0.00001460365,0.0003550917,0.9908053,0.001869095,0.0007308335,0.002682079,0.0001234376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3624534,0.00004397158,0.6370199,0.0003842585,0.00001875539,0.00004425025,0.000003225075,0.000008166724,0.00002415148],"genre_scores_gemma":[0.9627149,0.0000607549,0.03702138,0.00009251968,0.00008926664,0.000002204255,0.000004771854,0.00001019592,0.000004045376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6002615,"threshold_uncertainty_score":0.279176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04055966813881925,"score_gpt":0.2397190774545866,"score_spread":0.1991594093157673,"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."}}