{"id":"W3093008217","doi":"10.1002/met.1953","title":"Malaria and meningitis under climate change: initial assessment of climate information service in Nigeria","year":2020,"lang":"en","type":"article","venue":"Meteorological Applications","topic":"Malaria Research and Control","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Global Affairs Canada; Department for International Development, UK Government; International Development Research Centre; Government of Canada","keywords":"Malaria; Climate change; Early warning system; Meningitis; Warning system; Geography; Environmental science; Ecology; Medicine; Biology; Immunology; Pediatrics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003058392,0.0001011765,0.0002815993,0.00007318514,0.00005910249,0.00002452581,0.00008978568,0.0001062396,0.0002680174],"category_scores_gemma":[0.00005299534,0.00008199623,0.00003526911,0.0003717386,0.00005159781,0.0001676142,0.0001322681,0.0002223675,0.00002904424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002217088,"about_ca_system_score_gemma":0.00003468024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002313653,"about_ca_topic_score_gemma":0.00002090929,"domain_scores_codex":[0.9989266,0.00006848381,0.0003539394,0.0001749264,0.0002043348,0.0002716529],"domain_scores_gemma":[0.9993654,0.00009468207,0.00009542549,0.000147469,0.0001108316,0.0001862298],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002116896,0.0007789926,0.09420186,0.001555419,0.0001763389,0.00002795604,0.001378074,0.00009577202,0.03131195,0.7681741,0.00008834639,0.1000943],"study_design_scores_gemma":[0.003476783,0.0007600284,0.9734963,0.0000285637,0.00006757408,0.00001658554,0.0003757508,0.01613441,0.0002673591,0.001815419,0.00339899,0.0001622893],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6601087,0.0003185169,0.04886242,0.2522905,0.00004893289,0.007897349,0.0005419994,0.000287981,0.02964362],"genre_scores_gemma":[0.9898606,0.0002719221,0.004055044,0.004445114,0.00006807059,0.001151197,0.0001414463,0.000005653037,9.833957e-7],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8792944,"threshold_uncertainty_score":0.3343709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0449273534537175,"score_gpt":0.3422412484735754,"score_spread":0.2973138950198579,"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."}}