{"id":"W3013056994","doi":"10.2196/18828","title":"Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study","year":2020,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":415,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Mean squared error; Data mining; Metric (unit); Incidence (geometry); Outbreak; Statistics; Computer science; Health care; Medicine; Environmental health; Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003461764,0.0002695218,0.001266634,0.0003879662,0.0002023087,0.00007679676,0.0007467919,0.00005468576,0.00006763113],"category_scores_gemma":[0.007799245,0.0002609793,0.000029853,0.003133878,0.0001690855,0.0007273755,0.001356797,0.0003637479,0.000001134692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000875252,"about_ca_system_score_gemma":0.0007251215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001982905,"about_ca_topic_score_gemma":0.01355425,"domain_scores_codex":[0.9954002,0.0009231888,0.001025104,0.001391231,0.0006184213,0.0006418612],"domain_scores_gemma":[0.995564,0.0007975367,0.0005021679,0.001685829,0.00007952536,0.001370941],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003898193,0.0003251598,0.9529732,0.0005382827,0.0002660037,0.00004950712,0.005604511,0.00002225294,0.000004366988,0.000004817195,0.0006469922,0.03917501],"study_design_scores_gemma":[0.00236524,0.001320207,0.89788,0.00002434584,0.00002931826,0.00001014878,0.005017039,0.07736084,3.585277e-8,9.207454e-7,0.01579644,0.0001955157],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981766,0.003996849,0.0005900937,0.01084154,0.00004299847,0.0007195578,0.001584487,0.0001729227,0.0002855238],"genre_scores_gemma":[0.988777,0.0007983856,0.0008716313,0.003637954,0.00008907712,0.00002872533,0.005750191,0.00002700066,0.00001999623],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07733858,"threshold_uncertainty_score":0.9999843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1985095149059298,"score_gpt":0.4130092291816802,"score_spread":0.2144997142757504,"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."}}