{"id":"W2944123863","doi":"10.1016/j.jclepro.2019.05.073","title":"Renewable energy based mine reclamation strategy: A hybrid fuzzy-based network analysis","year":2019,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Land reclamation; Fuzzy logic; Fuzzy cognitive map; Process (computing); Computer science; Renewable energy; Closure (psychology); Environmental resource management; Environmental economics; Environmental science; Fuzzy set; Engineering; Fuzzy number; Artificial intelligence; Geography","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":[0.0003680605,0.0005421416,0.0006242334,0.0009310743,0.0005473149,0.000950942,0.0008154744,0.0008389509,0.002469607],"category_scores_gemma":[0.0008311768,0.0002369353,0.0007122291,0.0005464465,0.0002667656,0.0009769361,0.0003368579,0.0003242995,0.0001370002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001037884,"about_ca_system_score_gemma":0.0006439805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01868554,"about_ca_topic_score_gemma":0.01408951,"domain_scores_codex":[0.9998629,0.00003482933,0.00000709229,0.00003918783,0.00003357711,0.00002225553],"domain_scores_gemma":[0.999727,0.0001342167,0.00003878534,0.000008574369,0.00007916005,0.00001233652],"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":[0.00002909919,0.0000209577,0.0006204137,0.0000191271,0.00002627559,0.00004574201,0.00001873535,0.9873692,0.0007814852,0.002321904,0.0001398133,0.008607198],"study_design_scores_gemma":[9.759333e-7,0.000003925352,0.0001019739,0.000001162873,0.000005537324,0.000002972232,0.000005180249,0.9993336,0.00006963628,0.0004429967,0.00003060146,0.000001380614],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2703961,0.0004045134,0.7131275,0.0004308348,0.00006378243,0.00008663489,0.0002136914,0.0001812106,0.01509569],"genre_scores_gemma":[0.9822891,0.0001389249,0.01485888,0.00002223164,0.00001502259,0.00003885967,0.00005411337,0.000009849093,0.002573068],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01868554,"threshold_uncertainty_score":0.0371536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01467610715331856,"score_gpt":0.2316117176464063,"score_spread":0.2169356104930877,"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."}}