{"id":"W2900950414","doi":"10.36487/acg_rep/1815_25_noriega","title":"Optimisation of the undercut level elevation in block caving mines using a mathematical programming framework","year":2018,"lang":"en","type":"article","venue":"","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Undercut; Elevation (ballistics); Integer programming; Linear programming; Block (permutation group theory); Net present value; Set (abstract data type); Computer science; Engineering; Mathematical optimization; Operations research; Mathematics; Structural 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":[0.0001459612,0.00006217538,0.00008814364,0.0000441454,0.00002481207,0.00001643878,0.00008028538,0.00007712466,0.00003042787],"category_scores_gemma":[0.00005641165,0.00005035877,0.00002360552,0.0001186543,0.00002793252,0.00006011028,0.00002639814,0.00006011394,0.000001572623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006175538,"about_ca_system_score_gemma":0.00000866158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002781696,"about_ca_topic_score_gemma":0.00005253229,"domain_scores_codex":[0.999563,0.000006000159,0.000211096,0.00006585294,0.00004477518,0.0001093],"domain_scores_gemma":[0.9997553,0.00003896106,0.00003328683,0.0001408006,0.00001976252,0.00001189259],"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":[0.00005518091,0.0005133501,0.07611629,0.002446597,0.0002750748,0.000003841557,0.03826185,0.3137831,0.2060328,0.2426574,0.001562564,0.1182919],"study_design_scores_gemma":[0.00006666311,0.00001778987,0.0008770051,0.0002824813,0.000009241126,0.000007316855,0.0003056509,0.9576395,0.0305888,0.009973081,0.0001089618,0.0001235194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8012862,0.000004590674,0.1977138,0.00002680063,0.00005142499,0.0001141273,4.495004e-7,0.00007034671,0.0007322041],"genre_scores_gemma":[0.7037464,0.000001233349,0.2961779,0.000008617781,0.0000347789,0.000004000794,2.875184e-7,0.000009871416,0.00001697125],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6438563,"threshold_uncertainty_score":0.2053571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06432523652120502,"score_gpt":0.2744971261398647,"score_spread":0.2101718896186597,"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."}}