{"id":"W4403876679","doi":"10.3390/min14111094","title":"Reviving Riches: Unleashing Critical Minerals from Copper Smelter Slag Through Hybrid Bioleaching Approach","year":2024,"lang":"en","type":"article","venue":"Minerals","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; National Research Council Canada; Rio Tinto (Canada); Centre Technologique des Résidus Industriels; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Bioleaching; Smelting; Slag (welding); Copper; Metallurgy; Copper slag; Mineral; Environmental science; Mining engineering; Materials science; Geology","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":[0.0002247044,0.000649879,0.0004724125,0.0006515681,0.0002593137,0.0006717248,0.0004130483,0.000476576,0.001200479],"category_scores_gemma":[0.0001884647,0.0002602259,0.0005875477,0.0003210234,0.0003206576,0.0006302774,0.000843254,0.0006307341,0.0005990455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003040872,"about_ca_system_score_gemma":0.0002902566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007389354,"about_ca_topic_score_gemma":0.002201602,"domain_scores_codex":[0.9997578,0.00001755746,0.00001442077,0.00005623706,0.00008056463,0.00007335423],"domain_scores_gemma":[0.9999089,0.000009003366,0.00002391957,0.00001363848,0.00002369385,0.00002074555],"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":[0.00005895198,0.00002438027,0.0001205769,0.0001271818,0.00001210751,0.00007577465,0.00002878586,0.0001988175,0.9933649,0.0001269116,0.0001009086,0.005760768],"study_design_scores_gemma":[0.000007937506,0.0001794854,0.0004918537,0.000009200171,0.00001594309,0.00009205925,0.00004179767,0.0008940785,0.994989,0.00008331634,0.003186292,0.00000912338],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9580379,0.004010849,0.03203997,0.0002777615,0.000164817,0.0001541496,0.0004458564,0.0006871877,0.004181431],"genre_scores_gemma":[0.9757589,0.002117442,0.01541407,0.0001831031,0.00003300878,0.00008406794,0.0004705943,0.0001343613,0.00580439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001200479,"threshold_uncertainty_score":0.004015982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03256546219386277,"score_gpt":0.2836890433947861,"score_spread":0.2511235812009233,"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."}}