{"id":"W4365799806","doi":"10.13102/sitientibus.vi22.8791","title":"ESTIMANDO A FAVORABILIDADE PARA RECURSOS MINERAIS NA BACIA DE IRECÊ PELOS MÉTODOS LÓGICA NEBULOSA E PESOS DAS EVIDÊNCIAS","year":2022,"lang":"pt","type":"article","venue":"Sitientibus","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Geological Survey of Canada","funders":"","keywords":"Humanities; Geography; Biology; Art","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":[0.02409546,0.001202091,0.001620792,0.003404205,0.0004411543,0.00376159,0.001522261,0.002267786,0.001936956],"category_scores_gemma":[0.09913653,0.0007039631,0.002637555,0.002475011,0.001109133,0.002490459,0.001459858,0.001253037,0.0002454074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001624539,"about_ca_system_score_gemma":0.002636403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01398951,"about_ca_topic_score_gemma":0.01464963,"domain_scores_codex":[0.9915612,0.004829083,0.0006863353,0.001249623,0.001509357,0.0001644925],"domain_scores_gemma":[0.9273112,0.06284634,0.003598795,0.00204096,0.003925505,0.0002772217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004483455,0.0002838547,0.3398954,0.007315055,0.009705834,0.0004397471,0.001148205,0.3035477,0.01688436,0.01194363,0.0009433648,0.3034094],"study_design_scores_gemma":[0.0009377138,0.003895904,0.1713651,0.003395036,0.0115631,0.0009052674,0.002815241,0.6755302,0.0303395,0.08591063,0.01298547,0.0003569276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6119661,0.02118406,0.3522924,0.004182745,0.0001489782,0.000514612,0.002524242,0.0004241778,0.006762719],"genre_scores_gemma":[0.9098756,0.003180583,0.0849123,0.0002496683,0.00004780361,0.0002366111,0.0005049597,0.00002954659,0.0009629354],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02409546,"threshold_uncertainty_score":0.1274305,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03031176999036444,"score_gpt":0.2787135089878639,"score_spread":0.2484017389974995,"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."}}