{"id":"W4313505965","doi":"10.1007/978-3-031-17425-4_80","title":"Cobalt–Nickel Separations Using Supported Liquid Membranes for End-of-Life Lithium-Ion Battery Recycling","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":"National Research Council Canada","funders":"","keywords":"Nickel; Cobalt; Membrane; Battery (electricity); Lithium (medication); Materials science; Ion; Lithium-ion battery; Inorganic chemistry; Chemistry; Metallurgy; Organic chemistry; Psychology; Thermodynamics; Physics","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":[],"category_scores_codex":[0.0002061213,0.0003704859,0.0005271522,0.0003673882,0.0001294615,0.00005674953,0.0001421204,0.0004670111,0.001315211],"category_scores_gemma":[0.00008427513,0.0004003152,0.0002304717,0.00009401093,0.00004843577,0.0002818371,0.00002311909,0.0002752557,0.0001714164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006382565,"about_ca_system_score_gemma":0.000218211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001105976,"about_ca_topic_score_gemma":0.0001241303,"domain_scores_codex":[0.9982449,0.000009685964,0.0009124048,0.000323823,0.0002601738,0.0002490309],"domain_scores_gemma":[0.9987376,0.0003600797,0.0002273405,0.0002799771,0.0002674239,0.0001275741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000756419,0.0001536127,0.00003185816,0.01795663,0.002886124,0.00003200974,0.001634623,0.4410686,0.1914318,0.1946104,0.1471882,0.002249705],"study_design_scores_gemma":[0.0009350004,0.0001785562,0.000005259469,0.0007155178,0.0004129235,0.0000299304,0.0002001262,0.09257252,0.07885969,0.00504243,0.8195207,0.001527321],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001952373,0.001166609,0.09372236,0.0004268035,0.004134361,0.001335389,0.0005172563,0.002228301,0.8945165],"genre_scores_gemma":[0.01944663,0.002580895,0.003839688,0.0003440896,0.0008256596,0.00008629229,0.001370463,0.0003822643,0.971124],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6723326,"threshold_uncertainty_score":0.9998448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08270174938947107,"score_gpt":0.3127417339413094,"score_spread":0.2300399845518384,"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."}}