{"id":"W4281551947","doi":"10.1016/j.epidem.2022.100583","title":"Modeling waning and boosting of COVID-19 in Canada with vaccination","year":2022,"lang":"en","type":"article","venue":"Epidemics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; National Sleep Foundation; Hungarian Scientific Research Fund; Institute of Population and Public Health; James Merrill House; California State University, Northridge; Centers for Disease Control and Prevention; American Institute of Mathematics; National Science Foundation","keywords":"Vaccination; Herd immunity; Pandemic; Coronavirus disease 2019 (COVID-19); Medicine; Context (archaeology); Public health; Population; Environmental health; Social distance; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Immunology; Virology; Infectious disease (medical specialty); Biology; Disease; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002113525,0.0001068922,0.0003759062,0.00005541581,0.000188795,0.00000268811,0.0001136659,0.00002256959,0.00003486621],"category_scores_gemma":[0.02032828,0.00009196594,0.00001859046,0.0002179294,0.00001295058,0.00003942452,0.000261063,0.0002618634,5.598583e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001401033,"about_ca_system_score_gemma":0.0005990798,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6907481,"about_ca_topic_score_gemma":0.7381997,"domain_scores_codex":[0.9986019,0.0002552679,0.0004862478,0.0002269495,0.000210125,0.0002195745],"domain_scores_gemma":[0.993012,0.00654779,0.0002026627,0.0001323177,0.00003336311,0.00007192533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004631851,0.00001924498,0.4375477,0.0002597904,0.00002277905,0.000019333,0.00106287,0.5468819,0.00002272627,0.01191562,0.0008498676,0.001351848],"study_design_scores_gemma":[0.0005554484,0.00007781675,0.004768771,0.00003485339,0.00002323256,0.00001266507,0.003995486,0.8971484,0.000008453381,0.09247676,0.0006915221,0.0002066571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9582688,0.0003869251,0.03769824,0.003147312,0.00003558175,0.0002149758,0.00001451197,0.00003046025,0.0002032591],"genre_scores_gemma":[0.9903099,0.00003677391,0.008088745,0.001493322,0.00001350374,0.00003195519,0.000002809854,0.00001148714,0.00001151939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4327789,"threshold_uncertainty_score":0.9879239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2362257613705684,"score_gpt":0.3924270771782572,"score_spread":0.1562013158076888,"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."}}