{"id":"W3186327110","doi":"10.3390/ijerph18157841","title":"The Global Interest in Vaccines and Its Prediction and Perspectives in the Era of COVID-19. Real-Time Surveillance Using Google Trends","year":2021,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Autoregressive integrated moving average; Pandemic; Exponential smoothing; Quarter (Canadian coin); Medicine; Poliomyelitis; Econometrics; Time series; Virology; Statistics; Demography; Geography; Disease; Mathematics; Infectious disease (medical specialty)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000994964,0.0003488689,0.0002508414,0.002995321,0.0001017293,0.0009742726,0.0002474597,0.0003396586,0.0009563622],"category_scores_gemma":[0.004613497,0.0001235968,0.0006402044,0.003725512,0.0001700123,0.001217102,0.0004929789,0.0004522719,0.0004617207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006885372,"about_ca_system_score_gemma":0.0004938843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0274135,"about_ca_topic_score_gemma":0.02300178,"domain_scores_codex":[0.9996203,0.00009896584,0.00004192244,0.00008656537,0.0001100836,0.00004207713],"domain_scores_gemma":[0.9977882,0.0007477967,0.000813671,0.0001193308,0.0004243805,0.0001065693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002017814,0.00004617596,0.9122609,0.0006570652,0.0002251039,0.000225729,0.0005335182,0.01149395,0.001044917,0.002249668,0.0131052,0.05795589],"study_design_scores_gemma":[0.0000100623,0.0001435577,0.9109563,0.0002788788,0.0001689965,0.0003625387,0.001388373,0.05993648,0.001795217,0.001938689,0.02297992,0.00004105159],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8855739,0.009069062,0.005960406,0.004527906,0.0001992961,0.0001034839,0.08346274,0.0004446568,0.01065839],"genre_scores_gemma":[0.9737317,0.001760996,0.003547945,0.0001440796,0.00009225436,0.00003721648,0.01987884,0.00002843379,0.0007783614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0274135,"threshold_uncertainty_score":0.05450785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1278077845905315,"score_gpt":0.4224573940808524,"score_spread":0.2946496094903209,"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."}}