{"id":"W2900316127","doi":"10.4136/ambi-agua.2270","title":"Quality of the water fluoridation and municipal-level indicators in a Brazilian metropolitan region","year":2018,"lang":"en","type":"article","venue":"Ambiente e Agua - An Interdisciplinary Journal of Applied Science","topic":"Dental Health and Care Utilization","field":"Dentistry","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cascades (Canada)","funders":"Fundação de Amparo à Pesquisa e Inovação do Espírito Santo; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Water fluoridation; Fluoride; Spearman's rank correlation coefficient; Sanitation; Environmental health; Christian ministry; Population; Metropolitan area; Statistic; Medicine; Statistics; Geography; Demography; Environmental science; Mathematics; Environmental engineering; Chemistry; Political science","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":[0.001151847,0.0001863959,0.0003072353,0.001198599,0.0003502896,0.0007052043,0.0002429318,0.0002109235,0.0004303495],"category_scores_gemma":[0.004049114,0.0001898701,0.0003003302,0.002398297,0.0004416241,0.0002993642,0.0006166662,0.0001990377,0.00004495791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00076585,"about_ca_system_score_gemma":0.0007965223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05497281,"about_ca_topic_score_gemma":0.0712234,"domain_scores_codex":[0.9992777,0.0002389106,0.00007572537,0.0001332382,0.0001768272,0.00009766832],"domain_scores_gemma":[0.9980772,0.0003738289,0.0009017932,0.0001409981,0.0003781871,0.0001280745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002614154,0.00002508181,0.9924337,0.00003467266,0.000043917,0.00006541854,0.001023495,0.0001103202,0.0004873454,0.0001344455,0.00005865099,0.005556901],"study_design_scores_gemma":[0.0000011291,0.00003499089,0.9977824,0.00001745276,0.00002223832,0.00008508105,0.001081353,0.0002407125,0.000139319,0.00006132508,0.0005299209,0.000004084576],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984162,0.0003340811,0.0002015982,0.00006984479,0.000001489157,0.00001075374,0.000130542,0.00000492411,0.000830538],"genre_scores_gemma":[0.999635,0.00009311189,0.0001493008,0.000005082145,0.000001306934,0.000004184107,0.00006374884,8.743366e-7,0.00004742348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05497281,"threshold_uncertainty_score":0.1093056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03423265040069169,"score_gpt":0.3725310526113683,"score_spread":0.3382984022106766,"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."}}