{"id":"W4365130387","doi":"10.2196/41435","title":"Effect of Rapid Urbanization in Mainland China on the Seasonal Influenza Epidemic: Spatiotemporal Analysis of Surveillance Data From 2010 to 2017","year":2023,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Zhejiang Province; National Natural Science Foundation of China","keywords":"Urbanization; Mainland China; China; Transmission (telecommunications); Geography; Population; Socioeconomics; Environmental health; Demography; Medicine; Economic growth; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.00135787,0.0003882743,0.0003374271,0.0009496657,0.0003163431,0.000458482,0.0003906271,0.0002367345,0.0004210086],"category_scores_gemma":[0.001774176,0.000180752,0.001001633,0.001276666,0.0002555446,0.00042611,0.0005818465,0.0002683068,0.00008522297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001063632,"about_ca_system_score_gemma":0.001472715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0933643,"about_ca_topic_score_gemma":0.1012846,"domain_scores_codex":[0.9995481,0.0000942836,0.00006846678,0.0001206373,0.00008687337,0.00008153748],"domain_scores_gemma":[0.9989391,0.0002195367,0.0003565172,0.0001170215,0.0002462392,0.0001215471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005594351,0.00002005409,0.9912637,0.00003060862,0.0001372846,0.0001020618,0.0000958346,0.004698584,0.0003683226,0.0000903578,0.0004959661,0.002641256],"study_design_scores_gemma":[0.000005739791,0.00003197978,0.9778379,0.0000112814,0.00006693861,0.00004907147,0.000214915,0.02115826,0.000179809,0.00005056807,0.0003851239,0.000008387752],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975855,0.0001290463,0.0002548731,0.00007008996,0.000007356683,0.00001047608,0.00174849,0.00001169049,0.0001824843],"genre_scores_gemma":[0.9960948,0.000123119,0.00028627,0.00001712612,0.000006882156,0.00001303679,0.003388106,0.00000218181,0.00006853027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0933643,"threshold_uncertainty_score":0.1856417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2578842393777415,"score_gpt":0.4541615442524567,"score_spread":0.1962773048747152,"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."}}