{"id":"W4286001087","doi":"10.1002/cjce.24563","title":"Recovery of lithium from salt‐lake brine by liquid–liquid extraction using <scp>TBP‐FeCl<sub>3</sub></scp> based mixture solvent","year":2022,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Diluent; Brine; Solvent; Chemistry; Extraction (chemistry); Solubility; Data scrubbing; Potassium; Stripping (fiber); Chromatography; Sodium; Nuclear chemistry; Materials science; Waste management; Organic chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001777173,0.0002726348,0.0002190555,0.0002221624,0.0002611676,0.0002597636,0.0002832905,0.0002633854,0.0008773512],"category_scores_gemma":[0.0002522478,0.0001376534,0.0002253804,0.0002398064,0.0002491522,0.0004144781,0.000298208,0.0003594543,0.000487756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002349662,"about_ca_system_score_gemma":0.000435879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001271011,"about_ca_topic_score_gemma":0.00393346,"domain_scores_codex":[0.9998817,0.00001374662,0.000009896297,0.00002634823,0.00005348332,0.00001475133],"domain_scores_gemma":[0.9999205,0.00002117686,0.00001857156,0.000008344338,0.00002653991,0.000004774653],"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":[0.00004120227,0.000008864017,0.0002270092,0.00008024145,0.000005547595,0.00005067057,0.00002448867,0.0001093732,0.9936841,0.00006683033,0.00005693673,0.005644803],"study_design_scores_gemma":[0.000005041594,0.00006601123,0.0005237549,0.000005703064,0.00001088994,0.00004878986,0.00001617823,0.0008463066,0.9964415,0.00002665943,0.002002722,0.000006396334],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9399092,0.001785791,0.05387739,0.0001914772,0.00003414087,0.0001404888,0.0002870354,0.0003949169,0.003379496],"genre_scores_gemma":[0.9492642,0.001283643,0.04303655,0.0001030093,0.00001308015,0.00008406613,0.0004102062,0.00008135872,0.005723815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001271011,"threshold_uncertainty_score":0.002935052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008410779746245068,"score_gpt":0.1990226168243458,"score_spread":0.1906118370781007,"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."}}