{"id":"W4393255872","doi":"10.3390/min14040356","title":"Machine-Learning Analysis of the Canadian Royalties Grinding Circuit","year":2024,"lang":"en","type":"article","venue":"Minerals","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada; Natural Resources Canada","funders":"","keywords":"Grinding; Ball mill; Grind; Pentlandite; Gangue; Mill; Metallurgy; Environmental science; Pulp and paper industry; Chalcopyrite; Concentrator; Pyrrhotite; Materials science; Engineering; Mechanical engineering; Sulfide","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001951971,0.0001184714,0.0001912998,0.0005041636,0.0001455224,0.0001224493,0.0001601178,0.00006088267,0.0002095691],"category_scores_gemma":[0.0000374063,0.00008701759,0.0001480719,0.001221784,0.00002533759,0.00007087261,0.00001802962,0.0002491857,0.00001331339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001078911,"about_ca_system_score_gemma":0.00004135106,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02914149,"about_ca_topic_score_gemma":0.126741,"domain_scores_codex":[0.9992707,0.00002252145,0.0001914081,0.0001291997,0.0001417728,0.000244429],"domain_scores_gemma":[0.9997046,0.00004581911,0.00001835467,0.0001385535,0.00001867339,0.00007402744],"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":[6.837138e-7,0.000003612223,0.03760036,0.0003490932,0.001118519,0.00001720348,0.00259893,0.9225817,0.02524594,0.003987346,0.00291141,0.003585239],"study_design_scores_gemma":[0.00007496723,0.000009153592,0.006487926,0.0002366056,0.0006730886,0.000006760365,0.0001110814,0.9379303,0.00307258,0.0002611402,0.05080402,0.0003324175],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9333354,0.003988881,0.0001165166,0.000136845,0.0005502625,0.00006023923,0.0000355437,0.0002412887,0.06153502],"genre_scores_gemma":[0.9920142,0.00001661585,0.00003378872,0.00002424704,0.00007950303,0.000004916111,0.00001547546,0.00002372264,0.007787501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09759952,"threshold_uncertainty_score":0.9773235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01635684165952174,"score_gpt":0.218733853796629,"score_spread":0.2023770121371072,"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."}}