{"id":"W2769416572","doi":"10.36487/acg_rep/1710_26_pourrahimian","title":"Determination of optimum drawpoint layout in block caving using sequential Gaussian simulation","year":2017,"lang":"en","type":"article","venue":"","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Block (permutation group theory); Profit (economics); Footprint; Gaussian; Computer science; Mining engineering; Industrial engineering; Engineering; Civil engineering; Operations research; Geology; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001145376,0.00006167706,0.00009961869,0.00007288677,0.00004531054,0.0000435651,0.00009508442,0.00006060721,0.0000277534],"category_scores_gemma":[0.00001691128,0.00006933726,0.00002439922,0.00001411994,0.00001366617,0.0002038497,0.00003494421,0.00004999195,0.000001596652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007464756,"about_ca_system_score_gemma":0.000006596415,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001926719,"about_ca_topic_score_gemma":0.0001293485,"domain_scores_codex":[0.9996011,0.000004043362,0.0001906479,0.00007366288,0.00003164337,0.00009894869],"domain_scores_gemma":[0.9996973,0.000009952403,0.00006169501,0.0002020768,0.00001116361,0.00001779651],"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":[0.000002683107,0.000005849248,0.004579367,0.00003265336,0.00000318107,0.000002244868,0.0002512359,0.9856917,0.005270227,0.0001893919,0.000003913512,0.003967502],"study_design_scores_gemma":[0.0001062904,0.000007428871,0.002070252,0.00003879983,0.000003709169,0.000001574346,0.00001673256,0.9877965,0.009700531,0.0001575189,0.00002298826,0.00007765957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9086624,0.000003586903,0.08627098,0.000006986942,0.0001024708,0.00006875733,0.000001430972,0.00006816209,0.004815163],"genre_scores_gemma":[0.9596844,0.000002519389,0.0402414,0.000002422702,0.00003201043,0.000001407233,0.000001475618,0.00001304827,0.00002129469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05102196,"threshold_uncertainty_score":0.2827491,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04034788359666042,"score_gpt":0.2979266320161511,"score_spread":0.2575787484194907,"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."}}