{"id":"W4327519117","doi":"10.2139/ssrn.4389592","title":"Mercury Risk Reduction in Artisanal and Small-Scale Gold Mining: A Fuzzy Ahp-Fuzzy Topsis Hybrid Analysis","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Gold mining; Fuzzy logic; TOPSIS; Mercury (programming language); Analytic hierarchy process; Computer science; Business; Environmental science; Data mining; Operations research; Engineering; Artificial intelligence; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001377792,0.0005086549,0.0006789688,0.001520754,0.0007320347,0.001289127,0.0006964533,0.0004762913,0.001588063],"category_scores_gemma":[0.001454992,0.0002318141,0.001246837,0.001325872,0.0003438137,0.0005302739,0.000552966,0.0004035252,0.0001031588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001036603,"about_ca_system_score_gemma":0.00134717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01754026,"about_ca_topic_score_gemma":0.01851907,"domain_scores_codex":[0.999275,0.0002213612,0.00004400259,0.00007567477,0.0003089317,0.00007508],"domain_scores_gemma":[0.9995023,0.0002676733,0.00003727155,0.00002012785,0.0001544427,0.00001815426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00059015,0.0004574615,0.01458453,0.0005385667,0.0006362409,0.0004627222,0.0004524207,0.7976047,0.01245364,0.004537762,0.001162883,0.1665189],"study_design_scores_gemma":[0.00001434315,0.0001392539,0.004532647,0.00001914799,0.00009730023,0.00003868358,0.0003552821,0.9907863,0.001800456,0.001897252,0.0003006439,0.00001867724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7155502,0.0004234881,0.2739986,0.0003158574,0.00005631187,0.0002281221,0.000258768,0.0001804956,0.008988157],"genre_scores_gemma":[0.9811198,0.00009222172,0.01765226,0.00001013118,0.000006035536,0.00002931864,0.00005331549,0.00000695841,0.001030034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01754026,"threshold_uncertainty_score":0.03487629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009741844621221381,"score_gpt":0.2195741227169009,"score_spread":0.2098322780956795,"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."}}