{"id":"W2900554782","doi":"10.14288/1.0340914","title":"Leading practice in tailings planning for high-throughput mining operations","year":2017,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tailings; Throughput; Computer science; Business; Risk analysis (engineering); Mining engineering; Operations management; Geology; Engineering; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002109274,0.00003406083,0.0001816069,0.0000346827,0.0003510437,0.0002090163,0.0002830282,0.00008799684,0.00001373106],"category_scores_gemma":[0.0001327731,0.000138324,0.00004057039,0.00003462828,0.00006276884,0.0008330852,0.00007294579,0.00009533809,0.000003596674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000731971,"about_ca_system_score_gemma":0.00002099049,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02937665,"about_ca_topic_score_gemma":0.09111565,"domain_scores_codex":[0.9994752,0.000006846748,0.0001095828,0.0001818204,0.00004409995,0.0001824058],"domain_scores_gemma":[0.9995377,0.00006759742,0.00006312782,0.0002415736,0.00005017487,0.0000398353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00004081737,0.0001611097,0.02742104,0.0005302242,0.0002204065,0.0003973351,0.008543535,0.06695545,0.002537502,0.0001644874,0.02971968,0.8633084],"study_design_scores_gemma":[0.002915421,0.0001885817,0.7945785,0.001173517,0.00009911162,0.00008878846,0.01059177,0.1799019,0.00004931022,0.0006829656,0.008831169,0.0008989574],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9840333,0.00006805897,0.01250287,0.00007961817,0.0001471075,0.0001655955,0.00003997603,0.0001138613,0.002849644],"genre_scores_gemma":[0.9530286,0.0000858364,0.04659155,0.00001618535,0.00003249154,0.00000157436,0.00001111158,0.00001754339,0.000215098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8624095,"threshold_uncertainty_score":0.9770868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01653771654250812,"score_gpt":0.219630933679368,"score_spread":0.2030932171368598,"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."}}