{"id":"W2421556773","doi":"10.1016/j.jenvman.2016.05.084","title":"Recovery of metals from a mixture of various spent batteries by a hydrometallurgical process","year":2016,"lang":"en","type":"article","venue":"Journal of Environmental Management","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":106,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada; Institut national de la recherche scientifique","keywords":"Leaching (pedology); Zinc; Cadmium; Reagent; Sulfuric acid; Chemistry; Nickel; Metal; Manganese; Cobalt; Metallurgy; Environmental chemistry; Environmental science; Materials science; Inorganic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001065705,0.0001150446,0.0002611309,0.00009289371,0.00001227071,0.000009329925,0.000138287,0.00003931227,0.001743249],"category_scores_gemma":[0.000005171143,0.00007957449,0.0001052163,0.0000532808,0.00004887592,0.000300689,0.00002689551,0.0000635813,0.0000165659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005684574,"about_ca_system_score_gemma":0.000003101709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.641801e-7,"about_ca_topic_score_gemma":5.623594e-7,"domain_scores_codex":[0.9989498,0.00001826317,0.000526647,0.00008620563,0.0003270181,0.00009207126],"domain_scores_gemma":[0.999523,0.00003878912,0.0002767831,0.0001009828,0.000007868486,0.00005261044],"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":[0.000401425,0.001202315,0.0009573402,0.0005210731,0.002411179,0.00009126873,0.0005882171,0.007771443,0.9474356,0.0001226165,0.01105811,0.02743943],"study_design_scores_gemma":[0.005948896,0.001419011,0.03084406,0.0008651002,0.001059056,0.0001465808,0.001854046,0.0005956168,0.7344425,0.00511383,0.2167601,0.0009511849],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9765279,0.001431842,0.01814011,0.0001973932,0.0002364886,0.0001290289,0.00007774738,0.00001187275,0.003247636],"genre_scores_gemma":[0.9963262,0.00188717,0.0006780705,0.00003296293,0.00002446096,0.000003541202,0.000003766593,0.00001335197,0.001030488],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.212993,"threshold_uncertainty_score":0.9991693,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004733284293630204,"score_gpt":0.1985084848205888,"score_spread":0.1937752005269586,"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."}}