{"id":"W1970849216","doi":"10.1016/j.vaccine.2010.09.016","title":"Time and motion study to compare electronic and hybrid data collection systems during the pandemic (H1N1) 2009 influenza vaccination campaign","year":2010,"lang":"en","type":"article","venue":"Vaccine","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto General Hospital; University of British Columbia; University of Toronto; Public Health Ontario; Public Health Agency of Canada","funders":"Canadian Institutes of Health Research","keywords":"Data collection; Vaccination; Pandemic; H1n1 pandemic; Coronavirus disease 2019 (COVID-19); Electronic data; Sample (material); Electronic systems; Immunization; Data collection system; Computer science; Medical emergency; Medicine; Statistics; Virology; Database; Infectious disease (medical specialty); Engineering; Immunology; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007212288,0.0001697752,0.0002999289,0.0001451859,0.0002103406,0.00006687188,0.0001755196,0.00002417796,0.00006434726],"category_scores_gemma":[0.0002467669,0.0001275482,0.0000139613,0.0003048603,0.000006445779,0.0002248795,0.0002036135,0.0002793395,0.00003552883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008534503,"about_ca_system_score_gemma":0.00005577678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002485973,"about_ca_topic_score_gemma":0.001144084,"domain_scores_codex":[0.998642,0.0001197166,0.0002923103,0.0004597932,0.0002240741,0.0002621377],"domain_scores_gemma":[0.9986978,0.00007603345,0.0001090658,0.0008411221,0.0001301574,0.000145889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000521671,0.0002377339,0.9858455,0.0000992139,0.000109934,0.000009505249,0.0002885861,0.00006742886,0.007678928,0.000004953336,0.003360104,0.001776407],"study_design_scores_gemma":[0.002649633,0.000228373,0.983523,0.00003241667,0.000117219,0.0001817452,0.0002028492,0.01094423,0.00007390784,0.000005389637,0.001907567,0.000133683],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969526,0.0006330565,0.00006600205,0.0001436033,0.0001300546,0.001751763,0.0001486437,0.0001463658,0.00002788858],"genre_scores_gemma":[0.9990366,0.00005685287,0.00001614952,0.00008155053,0.0001946211,0.00003797002,0.0002777435,0.00002422617,0.000274299],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0108768,"threshold_uncertainty_score":0.5201263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0150404771670967,"score_gpt":0.2854255546330257,"score_spread":0.2703850774659289,"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."}}