{"id":"W3132063415","doi":"10.1101/2021.02.11.21251601","title":"Implications of climatic and demographic change for seasonal influenza dynamics and evolution","year":2021,"lang":"en","type":"preprint","venue":"medRxiv","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Institutes of Health; James S. McDonnell Foundation","keywords":"Climate change; Geography; Pandemic; Population; Population growth; Seasonal influenza; Climatology; Demography; Coronavirus disease 2019 (COVID-19); Ecology; Biology; Infectious disease (medical specialty); Medicine; Disease","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009299283,0.0002798351,0.0002828937,0.0003232219,0.0004397335,0.001355332,0.0004398171,0.0006427066,0.007384533],"category_scores_gemma":[0.004790811,0.0001616457,0.0005294704,0.0005392051,0.0005534635,0.001417748,0.0007649474,0.0006512412,0.0005894644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000674275,"about_ca_system_score_gemma":0.0004437369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006130307,"about_ca_topic_score_gemma":0.003741341,"domain_scores_codex":[0.9997212,0.0001692985,0.000008757536,0.00003867247,0.00002253638,0.00003960621],"domain_scores_gemma":[0.9987965,0.0006453017,0.0002388186,0.00008687314,0.00007944225,0.0001530563],"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":[0.0002584335,0.0001440543,0.2427002,0.0002799664,0.000282972,0.0006800034,0.0005157801,0.5650563,0.003271936,0.1544657,0.009518125,0.02282654],"study_design_scores_gemma":[0.00006573327,0.0001212857,0.1106362,0.00006456592,0.00006455028,0.0003535676,0.0008107245,0.6646698,0.0004667724,0.2144731,0.008219952,0.00005371127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9172929,0.001436299,0.04330255,0.0110867,0.0002347333,0.00003526251,0.002615865,0.0001587004,0.02383699],"genre_scores_gemma":[0.9963717,0.0004448124,0.001785336,0.0001621932,0.00005493646,0.00001231321,0.0002924034,0.00002107612,0.0008551046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007384533,"threshold_uncertainty_score":0.02470374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2750994059991882,"score_gpt":0.4277131250248402,"score_spread":0.152613719025652,"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."}}