{"id":"W4399518692","doi":"10.1101/2024.06.10.24308663","title":"Optimization of an adult immunization program in Canada","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; Public Health Agency of Canada; University of Saskatchewan; University of Alberta; Institute of Health Economics","funders":"","keywords":"Immunization; Portfolio; Population; Budget constraint; Health care; Medicine; Actuarial science; Business; Economics; Environmental health; Finance; Immunology; Economic growth; Microeconomics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001436923,0.0009772261,0.0007477622,0.0009143426,0.0007471032,0.001476059,0.001213389,0.0006964818,0.00476428],"category_scores_gemma":[0.003703016,0.0005245146,0.0007676203,0.001347505,0.000532729,0.0005869198,0.0006917383,0.0007120771,0.0001953203],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0353353,"about_ca_system_score_gemma":0.04787274,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.927035,"about_ca_topic_score_gemma":0.9098903,"domain_scores_codex":[0.9988297,0.000357973,0.00003033719,0.0001361221,0.0002123719,0.0004334887],"domain_scores_gemma":[0.9990396,0.0003486438,0.00009982318,0.00002975987,0.0003213496,0.0001608684],"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":[0.000222355,0.0001091076,0.0056932,0.0001616905,0.00008985908,0.00009325599,0.00005559193,0.9673924,0.0004767047,0.004542239,0.0024267,0.01873683],"study_design_scores_gemma":[0.000350323,0.0004376887,0.01749339,0.0001096295,0.0001941498,0.00005265246,0.0003291465,0.9646434,0.00109904,0.00514121,0.01009975,0.00004979471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8432447,0.003177933,0.06998441,0.003563287,0.000110821,0.002197606,0.007324838,0.0004638876,0.06993263],"genre_scores_gemma":[0.9646683,0.000760884,0.02409095,0.0003282849,0.000009356551,0.0002486995,0.001284881,0.00003919551,0.008569469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07296503,"threshold_uncertainty_score":0.2563767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01389639562978459,"score_gpt":0.2885862652558306,"score_spread":0.274689869626046,"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."}}