{"id":"W3162464467","doi":"10.22541/au.161918947.77588494/v2","title":"The Epidemic Volatility Index: an early warning tool for epidemics","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"","keywords":"Volatility (finance); Coronavirus disease 2019 (COVID-19); Warning system; Pandemic; Outbreak; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Index (typography); Econometrics; Early warning system; Computer science; Actuarial science; Business; Economics; Medicine; Telecommunications; Virology; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002976879,0.001249429,0.001016787,0.005294833,0.0003513418,0.003460053,0.0009419727,0.0007549011,0.003031314],"category_scores_gemma":[0.01512474,0.0003761782,0.000687666,0.00260334,0.0004927759,0.002132016,0.001663055,0.001754827,0.001064375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005441827,"about_ca_system_score_gemma":0.0009740406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001786571,"about_ca_topic_score_gemma":0.001082643,"domain_scores_codex":[0.9981906,0.0005711234,0.0001922577,0.0002958479,0.0006639278,0.00008612147],"domain_scores_gemma":[0.9937016,0.003637203,0.001011331,0.0005135426,0.000860719,0.0002757172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000505606,0.0002844254,0.1074992,0.001004519,0.0005645539,0.0004456391,0.0005669073,0.08733325,0.008850074,0.05236845,0.07220125,0.6683762],"study_design_scores_gemma":[0.0001343778,0.0005059753,0.05050492,0.0005593543,0.0002595066,0.001724219,0.0003477504,0.7016501,0.01374955,0.1295819,0.1005386,0.0004437602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06586917,0.007407857,0.87143,0.004786678,0.001545947,0.0004258928,0.02153985,0.0122494,0.0147452],"genre_scores_gemma":[0.4711551,0.003254478,0.5079782,0.0006927004,0.001200165,0.0003684019,0.01146452,0.000649941,0.003236465],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005294833,"threshold_uncertainty_score":0.01574343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03940551374754808,"score_gpt":0.3447455207679163,"score_spread":0.3053400070203682,"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."}}