{"id":"W4200277334","doi":"10.1016/j.wasman.2021.12.033","title":"Urban mining of terbium, europium, and yttrium from real fluorescent lamp waste using supercritical fluid extraction: Process development and mechanistic investigation","year":2021,"lang":"en","type":"article","venue":"Waste Management","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Europium; Terbium; Yttrium; Supercritical fluid extraction; Fluorescence; Chemistry; Supercritical fluid; Extraction (chemistry); X-ray photoelectron spectroscopy; Fluorescence spectroscopy; Nitric acid; Tributyl phosphate; Inorganic chemistry; Materials science; Waste management; Chemical engineering; Oxide; Organic 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":[],"consensus_categories":[],"category_scores_codex":[0.0001000128,0.0001566049,0.0001737455,0.00008240111,0.00009425663,0.00008608757,0.00004917907,0.00005125446,0.00003147937],"category_scores_gemma":[0.00001785752,0.0001751543,0.00001637086,0.0001692865,0.00003488487,0.0002200524,0.00005400186,0.00007913159,0.000002421395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004895704,"about_ca_system_score_gemma":0.00002765832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007384908,"about_ca_topic_score_gemma":0.00001587885,"domain_scores_codex":[0.9989405,0.00003054995,0.0003668265,0.0002669069,0.0002328862,0.0001623905],"domain_scores_gemma":[0.9996305,0.00003514723,0.00002554906,0.0001202966,0.00009038237,0.00009815329],"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":[0.00009557785,0.0002617336,0.003511572,0.007373791,0.0005965896,0.0003391074,0.0141351,0.01368824,0.9310325,0.01254539,0.001954802,0.01446556],"study_design_scores_gemma":[0.00108295,0.00004226176,0.003380159,0.0006108184,0.0002114496,0.00004428067,0.01583085,0.1332487,0.8404233,0.0003274072,0.004219736,0.0005780276],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844871,0.0004019481,0.01224589,0.0000670054,0.0002852777,0.000143654,0.000005684605,0.00008391953,0.002279568],"genre_scores_gemma":[0.9881387,0.0002050695,0.0112552,0.00004780496,0.00008718573,0.00001514111,0.00004305467,0.0000248506,0.0001830133],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1195605,"threshold_uncertainty_score":0.7142584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02333284869508922,"score_gpt":0.2502534739674493,"score_spread":0.2269206252723601,"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."}}