{"id":"W4210499406","doi":"10.1007/978-3-030-92563-5_17","title":"An Innovative Separation Process for Spent Lithium-Ion Battery Using Three-Stage Electrodialysis","year":2022,"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 Toronto","funders":"","keywords":"Electrodialysis; Ethylenediaminetetraacetic acid; Manganese; Nickel; Cobalt; Chemistry; Lithium (medication); Inorganic chemistry; Ion exchange; Electrochemistry; Materials science; Metallurgy; Membrane; Electrode; Ion; Chelation","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":[0.00009965368,0.0003834351,0.0003151598,0.0002516729,0.0003183111,0.0007173329,0.0008417355,0.0005920011,0.001094821],"category_scores_gemma":[0.00008139147,0.0002862137,0.0004094341,0.0003383333,0.0002656264,0.001088556,0.0005713195,0.001003577,0.0008626954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005146929,"about_ca_system_score_gemma":0.0004282601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005854883,"about_ca_topic_score_gemma":0.001551368,"domain_scores_codex":[0.9998784,0.00000476326,0.000006248851,0.00003160324,0.00006157052,0.00001736192],"domain_scores_gemma":[0.9999735,0.000006440259,0.000003680586,0.000003632291,0.00000933002,0.000003363459],"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":[0.00004455079,0.0000441468,0.00004320932,0.0002162628,0.000006806975,0.00008015725,0.00005511771,0.0002035259,0.971764,0.001849917,0.0007302436,0.02496197],"study_design_scores_gemma":[0.00001156493,0.0001049565,0.0002456162,0.000007338853,0.00001244456,0.0002687409,0.00002173218,0.003328737,0.9740747,0.0003589003,0.02154751,0.00001763083],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4849137,0.0282651,0.4264902,0.001508775,0.001493475,0.0005527872,0.0009416455,0.002558031,0.0532763],"genre_scores_gemma":[0.7276108,0.012679,0.1603116,0.0007860085,0.0001526985,0.0002497004,0.0008834288,0.0003289508,0.09699778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001094821,"threshold_uncertainty_score":0.00373435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04240397588239933,"score_gpt":0.3027871749405879,"score_spread":0.2603831990581886,"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."}}