{"id":"W4382561700","doi":"10.1007/s11157-023-09661-4","title":"Potential utilization of fungi in biomining as biological engines for the alteration of sulfide and carbon matrices","year":2023,"lang":"en","type":"article","venue":"Reviews in Environmental Science and Bio/Technology","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Mitacs","keywords":"Sulfur; Carbon fibers; Sulfide; Environmental science; Environmental chemistry; Biochemical engineering; Waste management; Chemistry; Engineering; Computer science; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000643711,0.00005441075,0.0001249618,0.0002907704,0.00002967553,0.000005235759,0.00007527533,0.00006301548,0.000002621366],"category_scores_gemma":[0.00006065852,0.00003446348,0.00001171137,0.000641059,0.0002382963,0.00005951202,0.00004251392,0.0000506422,6.538463e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001653889,"about_ca_system_score_gemma":0.000003110052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006640106,"about_ca_topic_score_gemma":0.000005295282,"domain_scores_codex":[0.9995003,0.00001150229,0.0002102933,0.0001157083,0.00006494141,0.00009719347],"domain_scores_gemma":[0.9998566,0.00002836457,0.00004569568,0.00005676005,0.000002602993,0.00001001166],"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":[0.000002362284,0.000007641199,0.008610294,0.00003515697,0.000001107675,3.067929e-7,0.00003873474,0.0001173413,0.6631895,0.0001442594,7.945213e-7,0.3278525],"study_design_scores_gemma":[0.0007290459,0.000390281,0.1392162,0.0003682739,0.00002992593,0.00004116502,0.002512205,0.3962572,0.4489358,0.0009945855,0.01017253,0.0003528321],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9829274,0.01648299,0.0001952153,0.00008498531,0.00005642258,0.0002220451,0.00000202596,0.00001391462,0.00001504446],"genre_scores_gemma":[0.9317122,0.06800679,0.0002491891,0.000005163604,0.000005510365,0.00001512019,0.000001935103,0.000001860181,0.000002234721],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3961398,"threshold_uncertainty_score":0.140538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02897377000894929,"score_gpt":0.2775547179466412,"score_spread":0.2485809479376919,"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."}}