{"id":"W4200012999","doi":"10.3390/vaccines10010017","title":"COVID-19 Seroprevalence in Canada Modelling Waning and Boosting COVID-19 Immunity in Canada a Canadian Immunization Research Network Study","year":2021,"lang":"en","type":"article","venue":"Vaccines","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; McGill University; York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Immunization Research Network","keywords":"Seroprevalence; Vaccination; Immunity; Herd immunity; Coronavirus disease 2019 (COVID-19); Medicine; Immunization; Booster (rocketry); Immunology; Population; Pandemic; Virology; Disease; Infectious disease (medical specialty); Environmental health; Immune system; Antibody; Serology; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001819583,0.0008285401,0.0007129849,0.001383217,0.0017085,0.001412126,0.00215076,0.0007114734,0.003143432],"category_scores_gemma":[0.003521854,0.0005596863,0.001504517,0.002169542,0.0006742021,0.0004823154,0.0007833439,0.0008917447,0.0003007666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04874475,"about_ca_system_score_gemma":0.0442142,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9975715,"about_ca_topic_score_gemma":0.9961075,"domain_scores_codex":[0.9991199,0.0002168883,0.00004074768,0.0001654987,0.0001211297,0.000335782],"domain_scores_gemma":[0.9983083,0.0003384797,0.0001984379,0.00008121839,0.0008118661,0.0002617527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007817905,0.0002655138,0.6130423,0.0003545807,0.0009713061,0.0005234237,0.001200165,0.3373526,0.001396091,0.008250569,0.01414995,0.02171164],"study_design_scores_gemma":[0.0003008012,0.0002488992,0.3489351,0.000273552,0.0006677796,0.0001625236,0.001979921,0.6300334,0.0007167336,0.002264988,0.01424656,0.0001696289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9611993,0.001754556,0.009027572,0.001560787,0.0000670149,0.0003294106,0.01777635,0.0001821494,0.008102952],"genre_scores_gemma":[0.9852261,0.0007870243,0.00463544,0.0001745208,0.000009340193,0.0001320414,0.004099826,0.00003345579,0.00490221],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04874475,"threshold_uncertainty_score":0.3536696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1126043439176654,"score_gpt":0.3728677344603287,"score_spread":0.2602633905426633,"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."}}