{"id":"W4410763004","doi":"10.1098/rsos.241261","title":"Large-scale epidemiological modelling: scanning for mosquito-borne diseases spatio-temporal patterns in Brazil","year":2025,"lang":"en","type":"article","venue":"Royal Society Open Science","topic":"Mosquito-borne diseases and control","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Generalitat de Catalunya; Wellcome Trust","keywords":"Chikungunya; Dengue fever; Geography; Arbovirus; Spatial epidemiology; Outbreak; Environmental health; Environmental resource management; Cartography; Epidemiology; Biology; Virology; Environmental science; Medicine","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":[0.001144353,0.0003730744,0.0003750866,0.0006364132,0.0002698761,0.0008696276,0.000714983,0.0003797446,0.0006841273],"category_scores_gemma":[0.006878534,0.0002738898,0.000879416,0.0008809621,0.0003512365,0.0005910387,0.0008523713,0.0003734047,0.00009246714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001172353,"about_ca_system_score_gemma":0.001434677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1576183,"about_ca_topic_score_gemma":0.1357013,"domain_scores_codex":[0.9996272,0.0001884948,0.00002676124,0.00008235884,0.00003314685,0.00004197306],"domain_scores_gemma":[0.9983276,0.001178592,0.0001821061,0.0001490201,0.0001033156,0.00005945093],"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":[0.00008644691,0.00008244976,0.2108634,0.0002096726,0.0002431127,0.0003938837,0.0006554822,0.7537289,0.001612765,0.007277412,0.002129848,0.02271665],"study_design_scores_gemma":[0.00001991335,0.00001917318,0.02714261,0.0000428431,0.00004453635,0.00009287761,0.0003316049,0.9672318,0.0002679311,0.003124429,0.001664923,0.00001737727],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9479964,0.001159262,0.04054914,0.001668728,0.00002480152,0.00008464298,0.004487247,0.0003696853,0.003660027],"genre_scores_gemma":[0.9863846,0.0004342155,0.0114342,0.00004785764,0.000007048709,0.00004496894,0.001333268,0.00002955749,0.0002842024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1576183,"threshold_uncertainty_score":0.3134016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02802496503977292,"score_gpt":0.351588162408214,"score_spread":0.3235631973684411,"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."}}