{"id":"W3135200564","doi":"10.3390/met11020371","title":"Hydrometallurgical Leaching of Copper Flash Furnace Electrostatic Precipitator Dust for the Separation of Copper from Bismuth and Arsenic","year":2021,"lang":"en","type":"article","venue":"Metals","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Rio Tinto; U.S. Department of Energy","keywords":"Arsenic; Copper; Bismuth; Leaching (pedology); Sulfuric acid; Chemistry; Sodium hydroxide; Antimony; Hydroxide; Inorganic chemistry; Metallurgy; Materials science; Environmental science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002009536,0.0001002936,0.0002424289,0.00004217933,0.00005633099,0.00003100986,0.00005510628,0.00005434922,0.0001446189],"category_scores_gemma":[0.0001391896,0.00007774726,0.00007338624,0.0001375891,0.00003310643,0.0001865269,0.00001109721,0.00009792302,0.00000986302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001309679,"about_ca_system_score_gemma":0.00003025874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003770108,"about_ca_topic_score_gemma":0.00003452892,"domain_scores_codex":[0.9992606,0.00004581476,0.0003193537,0.0001254683,0.0001406479,0.000108083],"domain_scores_gemma":[0.9991896,0.0004755739,0.00007951758,0.0001298308,0.00009123179,0.00003422338],"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":[0.00003936586,0.00006390973,0.0001364337,0.0001784888,0.0004173797,0.000001010535,0.001354247,0.02264998,0.9662055,0.000996216,0.005841848,0.002115582],"study_design_scores_gemma":[0.0008897051,0.00008066091,0.001233357,0.0000453607,0.00029718,0.00001626414,0.0004923147,0.1550921,0.7501968,0.000512736,0.09092531,0.0002181917],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9615943,0.006869955,0.02877332,0.0003146016,0.0001858238,0.0002492877,0.000050441,0.00004699227,0.001915221],"genre_scores_gemma":[0.9956642,0.0004237098,0.00197493,0.00004857269,0.00003418586,0.00002793302,0.00003530846,0.00001678836,0.001774417],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2160088,"threshold_uncertainty_score":0.3170441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01907945424691727,"score_gpt":0.2819196521836275,"score_spread":0.2628401979367102,"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."}}