{"id":"W4385840172","doi":"10.3390/met13081467","title":"Feasibility of Recovering Valuable and Toxic Metals from Copper Slag Using Iron-Containing Additives","year":2023,"lang":"en","type":"article","venue":"Metals","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Ferrosilicon; Slag (welding); Metallurgy; Smelting; Gravity separation; Environmental science; Copper; Settling; Waste management; Raw material; Tailings; Copper slag; Pyrometallurgy; Materials science; Alloy; Chemistry; Environmental engineering; Engineering","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":[0.0003623295,0.0001182454,0.0002743182,0.00009921552,0.00005874066,0.00004031348,0.00005542145,0.00005689105,0.0004452494],"category_scores_gemma":[0.0001657768,0.0001191116,0.00005398456,0.0002270128,0.000027989,0.0004396766,0.00002690022,0.00007791724,0.00003930158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003084619,"about_ca_system_score_gemma":0.00001660748,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000386426,"about_ca_topic_score_gemma":0.000025587,"domain_scores_codex":[0.9992003,0.00004414297,0.0002867043,0.0001796227,0.0001360382,0.0001531553],"domain_scores_gemma":[0.9995,0.0002096795,0.00005858952,0.0001399801,0.00004183379,0.00004991873],"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":[0.00003855801,0.00003469833,0.003232454,0.0003028737,0.000282288,0.000006558291,0.001929008,0.1451161,0.8436772,0.0001766379,0.001511188,0.003692515],"study_design_scores_gemma":[0.001282035,0.00008228653,0.02060168,0.0002162811,0.0002798326,0.00001487003,0.002921275,0.4757385,0.4817911,0.002120501,0.01413771,0.0008139078],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9924338,0.001151254,0.00210578,0.00001744964,0.0001929707,0.0001175493,0.00007047727,0.0002072728,0.003703384],"genre_scores_gemma":[0.997183,0.0001541519,0.002085165,0.00002098792,0.00004301571,0.00000956485,0.00002592279,0.00002118527,0.0004570118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.361886,"threshold_uncertainty_score":0.4875169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08000717126466927,"score_gpt":0.3193554439693705,"score_spread":0.2393482727047012,"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."}}