{"id":"W2077471080","doi":"10.1016/j.vaccine.2011.05.028","title":"“Wait and see” vaccinating behaviour during a pandemic: A game theoretic analysis","year":2011,"lang":"en","type":"article","venue":"Vaccine","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":87,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Guelph","funders":"Canadian Institutes of Health Research","keywords":"Herd immunity; Outbreak; Vaccination; Pandemic; Transmission (telecommunications); Outcome (game theory); Game theory; Nash equilibrium; Demography; Coronavirus disease 2019 (COVID-19); Economics; Medicine; Microeconomics; Disease; Computer science; Virology; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005429796,0.00104958,0.001482627,0.0009854776,0.001356174,0.002741661,0.002448787,0.00343595,0.01010316],"category_scores_gemma":[0.01938105,0.0008742316,0.001232458,0.0006346442,0.003351384,0.004069716,0.001676832,0.002782166,0.0004524172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003636685,"about_ca_system_score_gemma":0.002935645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01158887,"about_ca_topic_score_gemma":0.009194037,"domain_scores_codex":[0.9975018,0.001584884,0.00006380266,0.0002237258,0.000163148,0.0004626247],"domain_scores_gemma":[0.9788471,0.01745944,0.001391148,0.0004240518,0.0006561995,0.001222055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008748488,0.0005654526,0.01174118,0.0002985349,0.0004866653,0.0006589396,0.00168544,0.3228529,0.003447941,0.6337479,0.005945716,0.0176945],"study_design_scores_gemma":[0.0001790817,0.0005587931,0.004614781,0.00005148403,0.0002127715,0.0002847521,0.001539267,0.807,0.0004163535,0.1831852,0.001863577,0.00009388846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6546558,0.000646412,0.262532,0.009919521,0.0001708999,0.0006199642,0.0005526257,0.000134872,0.07076798],"genre_scores_gemma":[0.9827206,0.0002152879,0.00897994,0.000379147,0.00004175052,0.0001095721,0.00006189103,0.00002130079,0.007470658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01158887,"threshold_uncertainty_score":0.03379846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06209532959928124,"score_gpt":0.3421806373008356,"score_spread":0.2800853077015544,"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."}}