{"id":"W4293247024","doi":"10.23955/rkl.v17i1.23223","title":"Optimizing Gold Recovery of Artisanal Mining: A Lesson Learned from Kenya","year":2022,"lang":"en","type":"article","venue":"Jurnal Rekayasa Kimia & Lingkungan","topic":"Metal Extraction and Bioleaching","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Gold cyanidation; Kenya; Gold mining; Leaching (pedology); Sample (material); Gold ore; Concentrator; Environmental science; Mining engineering; Metallurgy; Cyanide; Engineering; Chemistry; Materials science; Political science; Chromatography","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005290469,0.0002360992,0.0003872691,0.0002286771,0.0001903065,0.00006736452,0.0003004703,0.00009619807,0.0003255684],"category_scores_gemma":[0.0001245911,0.0002506498,0.0002456184,0.0003214249,0.00002738957,0.0001970097,0.0001106286,0.000902914,0.00001664116],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001763376,"about_ca_system_score_gemma":0.00005339343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001104758,"about_ca_topic_score_gemma":0.00002188966,"domain_scores_codex":[0.9981399,0.0001270081,0.0005940041,0.0002990222,0.0004871256,0.0003528931],"domain_scores_gemma":[0.999124,0.0001817588,0.0002113862,0.0002886037,0.000037428,0.0001568284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002713493,0.0001344402,0.0008983255,0.00007349133,0.0002936049,0.00008153247,0.002031124,0.2451036,0.6394018,0.0002332921,0.001871184,0.1096063],"study_design_scores_gemma":[0.004030073,0.00116258,0.008021278,0.0005160692,0.0005607893,0.0002740787,0.00679298,0.3381072,0.2708763,0.001561101,0.365445,0.002652508],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989521,0.001168222,0.002203303,0.0002039159,0.001357966,0.0001043482,0.00004348456,0.0002258224,0.005171921],"genre_scores_gemma":[0.9945949,0.0001433297,0.003990822,0.0001333913,0.0003377902,0.00001304364,0.00004407268,0.00006257336,0.0006801206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3685255,"threshold_uncertainty_score":0.9999946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03329883451073985,"score_gpt":0.248357323768979,"score_spread":0.2150584892582391,"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."}}