{"id":"W4409148453","doi":"10.1080/21645515.2025.2485838","title":"Modeling the effects of improving varicella vaccination coverage on clinical and economic outcomes in Peru","year":2025,"lang":"en","type":"article","venue":"Human Vaccines & Immunotherapeutics","topic":"Herpesvirus Infections and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Merck Canada Inc. (Canada)","funders":"","keywords":"Medicine; Per capita; Proxy (statistics); Vaccination; Discounting; Demography; Chickenpox; Epidemiology; Pediatrics; Environmental health; Statistics; Population; Immunology; Internal medicine; Business","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":[0.001715558,0.0009630403,0.0006046779,0.0009618385,0.0002890771,0.001328992,0.001381663,0.001380661,0.00549372],"category_scores_gemma":[0.007109113,0.0006206837,0.001410632,0.001018012,0.0005142295,0.0008538846,0.00131186,0.0009277986,0.000252559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003009666,"about_ca_system_score_gemma":0.002118464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06038712,"about_ca_topic_score_gemma":0.03209092,"domain_scores_codex":[0.999247,0.0004929081,0.00002195083,0.0000792446,0.00003309432,0.0001258562],"domain_scores_gemma":[0.9972225,0.002045523,0.0003436005,0.00006263711,0.0002329867,0.00009272327],"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":[0.00009818385,0.00007356893,0.007348899,0.00007459198,0.00009995664,0.0001454222,0.00005072638,0.986511,0.0001803896,0.002709234,0.0005729177,0.002135061],"study_design_scores_gemma":[0.0001386143,0.0002343184,0.005317104,0.00006793551,0.0001554506,0.00005771377,0.0001344068,0.9876721,0.000147552,0.004148124,0.001896182,0.00003046777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9489561,0.002269418,0.01887237,0.003895964,0.00005329144,0.0002335423,0.005304072,0.0001860093,0.02022915],"genre_scores_gemma":[0.9903666,0.0008465662,0.003922536,0.0002096424,0.00002214019,0.0002268398,0.001153472,0.00003191567,0.003220266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06038712,"threshold_uncertainty_score":0.1200713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02574541809886799,"score_gpt":0.3476993414982323,"score_spread":0.3219539233993643,"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."}}