{"id":"W3034246971","doi":"10.1101/2020.06.09.20125724","title":"Estimating Force of Infection from Serologic Surveys with Imperfect Tests","year":2020,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Mosquito-borne diseases and control","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"European and Developing Countries Clinical Trials Partnership; Medical Research Council; Canadian Institutes of Health Research; Department of Epidemiology, Biostatistics and Occupational Health, McGill University; Department for International Development; European Commission; McGill University; Fundação de Amparo à Pesquisa do Estado de São Paulo; London School of Hygiene and Tropical Medicine","keywords":"Serology; Proxy (statistics); Dengue fever; Medicine; Outbreak; Econometrics; Statistics; Immunology; Virology; Mathematics; Antibody","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":[0.04371125,0.001333507,0.001771279,0.003310862,0.0007106077,0.002124432,0.002103992,0.001687883,0.002051081],"category_scores_gemma":[0.1948346,0.0008750757,0.001629038,0.002666252,0.002434487,0.003001595,0.002740967,0.001729469,0.0003919144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00158609,"about_ca_system_score_gemma":0.001122003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006171869,"about_ca_topic_score_gemma":0.005383097,"domain_scores_codex":[0.9701253,0.02020696,0.001820954,0.003275798,0.003761495,0.0008095594],"domain_scores_gemma":[0.716834,0.2218461,0.03284498,0.02364283,0.004153291,0.0006787889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0009935471,0.0002619495,0.4445387,0.0008981748,0.001880475,0.0004962151,0.002070843,0.22301,0.002941928,0.05334787,0.002323535,0.2672368],"study_design_scores_gemma":[0.0002265266,0.0009162087,0.225236,0.0006231595,0.0005290709,0.0009930813,0.0008324556,0.6043525,0.005294229,0.1521467,0.008573555,0.0002764399],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2077328,0.0009949515,0.7845338,0.0008222159,0.00007079064,0.0005454017,0.001473568,0.0002123583,0.003614214],"genre_scores_gemma":[0.8014494,0.0006357516,0.1924426,0.0003276436,0.0001640919,0.0007621238,0.001957808,0.0000398744,0.002220681],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04371125,"threshold_uncertainty_score":0.2311699,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0254816299791242,"score_gpt":0.2875232391581916,"score_spread":0.2620416091790674,"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."}}