{"id":"W7132860980","doi":"","title":"Enhanced Beneficiation of Ultramafic Nickel Ores Using Novel Reagents","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Minerals Flotation and Separation Techniques","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; University of Alberta","keywords":"Pentlandite; Nickel; Beneficiation; Sulfide minerals; Adsorption; Reagent; Mineral processing; Hydrometallurgy; Gangue; Sulfide","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001761135,0.0003969385,0.0002597416,0.0002787338,0.0001586749,0.0003997579,0.0004755324,0.0004534193,0.001512564],"category_scores_gemma":[0.0002101887,0.0002456192,0.0003881523,0.0001681138,0.0001617167,0.0004225651,0.0003472914,0.0005481186,0.0006800982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002340341,"about_ca_system_score_gemma":0.0001755958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002470792,"about_ca_topic_score_gemma":0.0007655778,"domain_scores_codex":[0.9998635,0.00001078883,0.00001051517,0.00003325418,0.00005148578,0.00003046818],"domain_scores_gemma":[0.999943,0.000009918987,0.00001968199,0.000004585454,0.0000117483,0.0000110213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009998485,0.00007486663,0.0001214428,0.0003623367,0.00001509498,0.0001156293,0.00004322374,0.0001782535,0.993651,0.0004177964,0.0002539536,0.004666546],"study_design_scores_gemma":[0.00001706113,0.000186883,0.0002875028,0.000009723969,0.00001186483,0.00008036388,0.00001265999,0.0006966152,0.9951679,0.00003550698,0.003487655,0.000006340483],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9729392,0.005117134,0.01089019,0.0003423197,0.0001668422,0.0001965719,0.0003608839,0.0004276101,0.009559113],"genre_scores_gemma":[0.9772708,0.003652678,0.01101706,0.0002230102,0.0000323902,0.000136391,0.0003298704,0.00005928339,0.007278611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001512564,"threshold_uncertainty_score":0.005060017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05165129366139568,"score_gpt":0.3769802881851015,"score_spread":0.3253289945237058,"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."}}