{"id":"W4387092120","doi":"10.1126/sciadv.adf7202","title":"Disentangling local and global climate drivers in the population dynamics of mosquito-borne infections","year":2023,"lang":"en","type":"article","venue":"Science Advances","topic":"Mosquito-borne diseases and control","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Quebec Automobile Insurance Corporation","funders":"Division of Mathematical Sciences; National Key Research and Development Program of China; National Institutes of Health; National Science Foundation","keywords":"Seasonality; Climatology; Population; Environmental science; Climate change; Geography; Warning system; Ecology; Biology; Environmental health; Computer 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002938822,0.00005804744,0.0001047962,0.00008106785,0.0001439028,0.00002216413,0.00009923508,0.00001521458,0.000003431467],"category_scores_gemma":[0.00009171102,0.00004026461,0.00002952042,0.001270378,0.0003587974,0.0002884037,0.00004195106,0.0000447143,0.000002419329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007267294,"about_ca_system_score_gemma":0.0000441056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008136658,"about_ca_topic_score_gemma":0.0005797583,"domain_scores_codex":[0.9991691,0.00001493696,0.0001359335,0.0001897442,0.0002821503,0.0002081804],"domain_scores_gemma":[0.9996808,0.00003856091,0.00004984331,0.0001374509,0.00003992068,0.00005341498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000262518,0.00004284146,0.9389521,0.00003689411,0.000002359396,0.00001023179,0.0001029492,0.002262438,0.0001031345,0.01257223,0.000004001148,0.04588459],"study_design_scores_gemma":[0.0003881527,0.0000933772,0.9300709,0.00005351446,0.00002707211,0.000008498535,0.003386588,0.06358921,0.00002306384,0.002266358,0.0000434744,0.00004977824],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976771,0.0002753933,0.0002885072,0.0009730696,0.0001488242,0.0001786804,0.00002595762,0.00002801,0.0004043999],"genre_scores_gemma":[0.9996881,0.0001360549,0.00004784832,0.00007442655,0.00002305653,0.000009449486,0.00001403461,0.000002210533,0.000004837068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06132677,"threshold_uncertainty_score":0.1641943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006877449707857834,"score_gpt":0.3093917887229477,"score_spread":0.3025143390150899,"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."}}