{"id":"W4405513202","doi":"10.1016/j.mineng.2024.109157","title":"Leaching and recovery of rare earth elements, copper, nickel, silver and gold from used smartphone circuit boards","year":2024,"lang":"en","type":"article","venue":"Minerals Engineering","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Institut National de la Recherche Scientifique","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Leaching (pedology); Nickel; Rare earth; Metallurgy; Copper; Printed circuit board; Materials science; Environmental science; Engineering; Electrical engineering","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":[0.0001642478,0.0001428115,0.0001774764,0.0000685382,0.00002325665,0.00007437412,0.00008317864,0.0000481019,0.00007864059],"category_scores_gemma":[0.00002418328,0.000137436,0.00003218326,0.0001351827,0.00002960122,0.000224772,0.0001508775,0.0001166664,0.000009722074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002503838,"about_ca_system_score_gemma":0.000002103244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004966367,"about_ca_topic_score_gemma":0.00002534359,"domain_scores_codex":[0.9991622,0.00001390009,0.000211837,0.0002788496,0.0001573058,0.0001759109],"domain_scores_gemma":[0.9997004,0.00006464613,0.00002690231,0.0001520878,0.000002338439,0.00005359992],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000535103,0.00001885743,0.0130597,0.0001613659,0.00007413176,0.00002047979,0.0004232038,0.004185508,0.9283715,0.0001211565,0.007989432,0.04556932],"study_design_scores_gemma":[0.00231577,0.0005817472,0.1309256,0.003142833,0.00038249,0.00003590949,0.0004073261,0.2871154,0.197766,0.001069925,0.3734601,0.002796924],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938171,0.001410192,0.002182924,0.00005102486,0.0001448911,0.0001211198,0.00001917725,0.0001749856,0.002078593],"genre_scores_gemma":[0.9929401,0.0005220544,0.003778049,0.00003207711,0.00004805574,0.00001037355,0.00001481272,0.00002642016,0.002628019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7306055,"threshold_uncertainty_score":0.5604477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0103235188711581,"score_gpt":0.2051355434811326,"score_spread":0.1948120246099745,"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."}}