{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002016097,0.0002050831,0.0002923116,0.0004127237,0.0004081444,0.0005449883,0.0002872641,0.0003898788,0.0003770537],"category_scores_gemma":[0.0001733806,0.0001190903,0.0003453126,0.000357467,0.0002527199,0.0003312527,0.0002458831,0.0002183799,0.0001889269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003959132,"about_ca_system_score_gemma":0.0005675096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001731735,"about_ca_topic_score_gemma":0.004839286,"domain_scores_codex":[0.9998872,0.00001760622,0.000008238046,0.00001644952,0.00004804735,0.00002243091],"domain_scores_gemma":[0.9999392,0.00001552151,0.00001446856,0.000007743864,0.00001932571,0.000003850932],"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":[0.000304322,0.00009133223,0.002876101,0.0003140652,0.0000288276,0.0002520689,0.0002278869,0.002911113,0.9765254,0.0008003509,0.0001034464,0.015565],"study_design_scores_gemma":[0.000006508838,0.00008601731,0.001593458,0.000009057083,0.00001789034,0.00008948582,0.0001145856,0.004172831,0.99296,0.000126154,0.0008187119,0.000005314776],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954948,0.00017683,0.003407341,0.00003258908,0.000003194661,0.00001168288,0.00004949288,0.00001934094,0.0008046933],"genre_scores_gemma":[0.9960346,0.0003287301,0.00212131,0.00001011298,0.000001805693,0.000007892241,0.00006546747,0.000008279474,0.001421844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001731735,"threshold_uncertainty_score":0.00344336,"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."}}