{"id":"W4404384776","doi":"10.1080/09593330.2024.2423906","title":"Selective leaching of rare earths, base metals and precious metals from used smartphones","year":2024,"lang":"en","type":"article","venue":"Environmental Technology","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec; 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); Base metal; Precious metal; Environmental science; Heavy metals; Metallurgy; Environmental chemistry; Waste management; Chemistry; Metal; Materials science; Engineering; Welding","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":[0.0002533519,0.0002373417,0.0003231783,0.0001936654,0.00009541575,0.00003110451,0.0002590077,0.0001881369,0.0007849638],"category_scores_gemma":[0.00002646754,0.0002153742,0.00008426289,0.0002640701,0.0005463383,0.0002325143,0.0005591203,0.0002895631,0.0001938676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000101813,"about_ca_system_score_gemma":0.000002771216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002080021,"about_ca_topic_score_gemma":0.00003027466,"domain_scores_codex":[0.9984836,0.00007959409,0.0003088769,0.0006170543,0.0002409736,0.0002698862],"domain_scores_gemma":[0.9993939,0.0001037339,0.00008547996,0.0003638435,7.727546e-7,0.00005228243],"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":[0.00002768587,0.0002336288,0.08636801,0.00004521981,0.0003299565,0.00008389151,0.0009451735,0.000180755,0.7526708,0.0005073279,0.001515437,0.1570922],"study_design_scores_gemma":[0.000535658,0.000463484,0.0373503,0.0001361154,0.000245438,0.00004003519,0.001157685,0.002348478,0.9160322,0.01848951,0.02250575,0.0006953451],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928863,0.001919261,0.002141305,0.0004152695,0.0001026764,0.0003715531,0.00005416314,0.0004687645,0.001640715],"genre_scores_gemma":[0.9934675,0.0003881002,0.005225796,0.00003916567,0.00001801481,0.00005235634,0.00002262872,0.00003496194,0.0007515395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1633614,"threshold_uncertainty_score":0.8782703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007325007088299295,"score_gpt":0.2165259915282807,"score_spread":0.2092009844399814,"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."}}