{"id":"W1984993336","doi":"10.1186/1471-2334-9-77","title":"A simulation analysis to characterize the dynamics of vaccinating behaviour on contact networks","year":2009,"lang":"en","type":"article","venue":"BMC Infectious Diseases","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada","keywords":"Vaccination; Incentive; Transmission (telecommunications); Medical microbiology; Turnover; Social contact; Infectious disease (medical specialty); Disease; Environmental health; Medicine; Demography; Computer science; Psychology; Immunology; Social psychology; Economics; Microeconomics","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":[0.001221317,0.0005945873,0.0004630735,0.001224753,0.0006025723,0.0006744807,0.0008297568,0.001125353,0.004055247],"category_scores_gemma":[0.007741748,0.0002548927,0.0007809008,0.0008378596,0.0005659506,0.0008783579,0.0006639994,0.0007416724,0.0002292228],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001595808,"about_ca_system_score_gemma":0.0008898761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01175231,"about_ca_topic_score_gemma":0.007124191,"domain_scores_codex":[0.9995853,0.0002183051,0.00001563179,0.00006228594,0.00005211162,0.00006636154],"domain_scores_gemma":[0.9945673,0.004180605,0.000457764,0.0002445507,0.0003122278,0.0002376795],"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":[0.00006001306,0.00008227822,0.007421439,0.00002676436,0.00004339906,0.0001149664,0.0001039337,0.9768975,0.0004877755,0.01134233,0.000486347,0.002933295],"study_design_scores_gemma":[0.000006912177,0.00001777475,0.0005315877,0.000004319602,0.000005925252,0.00001951298,0.00001887426,0.9975436,0.00007099161,0.001583933,0.0001940485,0.000002507826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8415214,0.0003142948,0.1401014,0.0008522801,0.00004114511,0.0002473104,0.0006449937,0.0001847411,0.01609249],"genre_scores_gemma":[0.9841546,0.0001519743,0.01329969,0.00004892348,0.00001337379,0.0001725304,0.0003110657,0.00001696008,0.00183077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01175231,"threshold_uncertainty_score":0.02336782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09436495239874627,"score_gpt":0.3914803835480951,"score_spread":0.2971154311493488,"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."}}