{"id":"W4406674464","doi":"10.3390/met15010082","title":"Sustainable Leaching of Cu, Ni, and Au from Waste Printed Circuit Boards Using Choline Chloride-Based Deep Eutectic Solvents","year":2025,"lang":"en","type":"article","venue":"Metals","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Canada Foundation for Innovation","keywords":"Choline chloride; Printed circuit board; Leaching (pedology); Deep eutectic solvent; Eutectic system; Chloride; Materials science; Nuclear chemistry; Waste management; Chemistry; Metallurgy; Environmental science; Organic chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002021348,0.0007334757,0.0003981404,0.0003821001,0.0001758773,0.0003732718,0.000276144,0.0003721366,0.0005196913],"category_scores_gemma":[0.0002683362,0.0002422305,0.0003641739,0.0003959972,0.0002111613,0.0003907124,0.000473095,0.0003532803,0.000393424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001662111,"about_ca_system_score_gemma":0.0002061552,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008051363,"about_ca_topic_score_gemma":0.002334431,"domain_scores_codex":[0.9997353,0.0000342855,0.00002696885,0.00006032277,0.00009690652,0.00004627313],"domain_scores_gemma":[0.999928,0.00001253606,0.00002110981,0.000007790859,0.00002278068,0.000007759271],"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":[0.00004956485,0.000009971073,0.0001549499,0.0001408982,0.000009241421,0.00007430653,0.00003178777,0.0001993357,0.9959543,0.00003172665,0.00003751105,0.003306436],"study_design_scores_gemma":[0.000002192024,0.0000964559,0.0003044401,0.0000069546,0.000009094779,0.00005136916,0.00002960245,0.0003236421,0.9984516,0.00001137456,0.0007092999,0.000004087307],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9855328,0.003325223,0.008241941,0.00007915337,0.00003275281,0.00004421801,0.000346135,0.0001754431,0.002222235],"genre_scores_gemma":[0.9836069,0.003308811,0.009597033,0.00006282207,0.00001086733,0.00004572199,0.0003621266,0.00005789422,0.002947781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008051363,"threshold_uncertainty_score":0.001738548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0206078375532182,"score_gpt":0.2734387318962892,"score_spread":0.252830894343071,"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."}}