{"id":"W4387789202","doi":"10.1007/978-3-031-38141-6_26","title":"Hydrometallurgical Ni/Co/Mn Alloy Dissolution from Spent Catalyst Tailings","year":2023,"lang":"en","type":"book-chapter","venue":"","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hatch (Canada)","funders":"","keywords":"Leaching (pedology); Tailings; Lime; Metallurgy; Alloy; Dissolution; Smelting; Coke; Catalysis; Metal; Materials science; Waste management; Hydrogen peroxide; Chemistry; Environmental science; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00008194619,0.0003585484,0.0003737374,0.0001835766,0.00006778563,0.00008915405,0.0001706293,0.0004109356,0.01193038],"category_scores_gemma":[0.00001545305,0.0003531262,0.0001718199,0.00005165054,0.00003930872,0.0001922041,0.00003192487,0.0004276288,0.01183189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001020068,"about_ca_system_score_gemma":0.00002537844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005377357,"about_ca_topic_score_gemma":0.0001884024,"domain_scores_codex":[0.9985905,0.000004819102,0.0004568268,0.0003675252,0.0003662939,0.0002140617],"domain_scores_gemma":[0.9993783,0.00007083905,0.00007611075,0.0002815455,0.0000503378,0.0001428206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009546398,0.0001472478,0.000013182,0.0007909118,0.002692017,0.0004829691,0.0008070042,0.02624569,0.02153182,0.3105518,0.630903,0.005738923],"study_design_scores_gemma":[0.0001784282,0.00001743466,0.0000189545,0.00007264998,0.00008548177,0.000009631551,0.00002031677,0.009813325,0.001181262,0.004066942,0.9839859,0.0005496797],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0003395215,0.0004803719,0.002540591,0.0001323908,0.001067228,0.0001890873,0.0001284514,0.001670935,0.9934514],"genre_scores_gemma":[0.0203466,0.001046494,0.0001479297,0.00008812457,0.0003438077,0.00001632209,0.002543567,0.0001335935,0.9753336],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3530829,"threshold_uncertainty_score":0.9998921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02637293289944426,"score_gpt":0.2498067191095061,"score_spread":0.2234337862100619,"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."}}