{"id":"W3217325711","doi":"10.3390/materproc2021005039","title":"Green Zero-Waste Metal Extraction and Recycling from Printed Circuit Boards","year":2021,"lang":"en","type":"article","venue":"","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Extraction (chemistry); Printed circuit board; Zero waste; Waste management; Electronic waste; Base metal; Choline chloride; Materials science; Metal; Metallurgy; Chemistry; Chromatography; Computer science; Engineering; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00005272995,0.00008738295,0.0001061907,0.0000393729,0.00004678445,0.0000623575,0.00002830581,0.0000658365,0.0008244379],"category_scores_gemma":[0.00003340928,0.00009075359,0.00002907331,0.0001125498,0.000008671868,0.0003226729,0.00001067497,0.0001309202,0.00005429159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001959637,"about_ca_system_score_gemma":0.00001512272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005919021,"about_ca_topic_score_gemma":0.0001438912,"domain_scores_codex":[0.9994656,0.00001450945,0.0001708772,0.0001533141,0.0001015141,0.00009412381],"domain_scores_gemma":[0.9997042,0.00005483969,0.00002055298,0.0001016568,0.00006121938,0.00005753732],"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":[0.00001160599,0.00005201335,0.001120479,0.00009268559,0.0002122007,0.00003788144,0.0006117743,0.003633437,0.9311751,0.002162723,0.002209371,0.05868074],"study_design_scores_gemma":[0.0006309418,0.0000173807,0.004760968,0.00004220017,0.00007668178,0.00008150908,0.001235079,0.05682645,0.8113942,0.003796513,0.120683,0.0004551068],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6536986,0.001122562,0.2172717,0.0002318851,0.0007592788,0.0000813855,0.000009688519,0.000656378,0.1261685],"genre_scores_gemma":[0.9884702,0.0002449297,0.001525191,0.00009303226,0.0000999476,0.000006021826,0.00002983958,0.00001710076,0.009513744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3347716,"threshold_uncertainty_score":0.9027017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02563946253249381,"score_gpt":0.2602874796140361,"score_spread":0.2346480170815423,"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."}}