{"id":"W3198422133","doi":"10.1016/j.idm.2021.08.006","title":"Regional and temporal patterns of influenza: Application of functional data analysis","year":2021,"lang":"en","type":"article","venue":"Infectious Disease Modelling","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Children's Hospital Research Institute of Manitoba; University of Manitoba","keywords":"Functional data analysis; Variance (accounting); Geography; Statistics; Random effects model; Demography; Cartography; Medicine; Meta-analysis; Mathematics; Sociology","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":[0.0002016355,0.0001071908,0.000322058,0.0002397528,0.00007165626,0.000009198478,0.00006351731,0.00004106494,0.00003490911],"category_scores_gemma":[0.0001134951,0.0001032604,0.0001110956,0.0004766085,0.00009527339,0.0001200326,0.0001675377,0.0001126348,0.000001961946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003510659,"about_ca_system_score_gemma":0.0002147089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004575199,"about_ca_topic_score_gemma":0.00006508223,"domain_scores_codex":[0.9986872,0.00004378499,0.000344514,0.0003557158,0.0004285321,0.0001402169],"domain_scores_gemma":[0.9984738,0.0001001526,0.0001333426,0.0006238582,0.0005248477,0.0001439877],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002227974,0.0002425669,0.9095526,0.0003401325,0.001126682,0.000009692582,0.00007043156,0.08665126,0.0005106562,0.000458516,0.00004342193,0.0007711911],"study_design_scores_gemma":[0.001238175,0.00004743529,0.3086512,0.00008577332,0.001862575,0.000007229456,0.00007956858,0.6856111,0.0002937161,0.0008430686,0.001137064,0.0001431319],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6757221,0.00205151,0.3216748,0.00008260026,0.00001338129,0.0001465859,0.0002009497,0.00002151044,0.00008663627],"genre_scores_gemma":[0.9984273,0.0002646724,0.0005478705,0.0001664156,0.0000661226,0.00002113431,0.0004679227,0.00001119758,0.00002736996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6009014,"threshold_uncertainty_score":0.4210835,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1518742526808132,"score_gpt":0.371282444764143,"score_spread":0.2194081920833298,"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."}}