{"id":"W4320009259","doi":"10.1007/978-3-031-22638-0_9","title":"Energy-Saving Green Technologies in the Mining and Mineral Processing Industry","year":2023,"lang":"en","type":"book-chapter","venue":"˜The œminerals, metals & materials series","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Pyrometallurgy; Mineral processing; Electrowinning; Base metal; Hydrometallurgy; Extractive metallurgy; Mining industry; Environmental science; Metallurgy; Copper; Mining engineering; Engineering; Materials science; Smelting; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001282718,0.0006579721,0.0002961629,0.0007696211,0.000624259,0.001576368,0.000483307,0.0009881585,0.01459924],"category_scores_gemma":[0.0001432084,0.0002150878,0.000314851,0.001668536,0.0006393465,0.002421242,0.0007583794,0.001388624,0.00515597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008459484,"about_ca_system_score_gemma":0.0009147323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001551043,"about_ca_topic_score_gemma":0.005534629,"domain_scores_codex":[0.9998786,0.00001044622,0.000003272961,0.00001551148,0.00007923936,0.00001284882],"domain_scores_gemma":[0.9999508,0.00002451218,0.000003184252,0.000003754701,0.00001338826,0.000004335951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003176231,0.00013797,0.0001049059,0.0007914358,0.00001218091,0.0001815201,0.0002583384,0.002061223,0.008380956,0.3802174,0.1897192,0.418103],"study_design_scores_gemma":[0.000002220215,0.00002030695,0.0002378097,0.0003077048,0.000005126558,0.0001802999,0.0001334699,0.001046439,0.003381825,0.06713251,0.9275447,0.000007618571],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.004979743,0.2427819,0.02525326,0.006194727,0.003909411,0.00006987033,0.0001838082,0.0002103715,0.7164169],"genre_scores_gemma":[0.01908155,0.1585712,0.009050475,0.001467283,0.0007610569,0.00003901322,0.0001558237,0.0001143162,0.8107594],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01459924,"threshold_uncertainty_score":0.04883933,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02936277248014013,"score_gpt":0.2426082179428171,"score_spread":0.2132454454626769,"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."}}