{"id":"W4404511292","doi":"10.3389/fmicb.2024.1475144","title":"Genomic tools for post-elimination measles molecular epidemiology using Canadian surveillance data from 2018–2020","year":2024,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Virology and Viral Diseases","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Public Health Agency of Canada","funders":"Public Health Agency of Canada","keywords":"Measles; Epidemiological surveillance; Molecular diagnostics; Virology; Molecular epidemiology; Genomics; Epidemiology; Coronavirus disease 2019 (COVID-19); Postmarketing surveillance; Computational biology; Biology; Genome; Genetics; Medicine; Infectious disease (medical specialty); Genotype; Gene; Vaccination; Disease","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":[0.002135745,0.0005967018,0.0003485219,0.00852762,0.001106032,0.001379022,0.0008922895,0.0002479118,0.002831023],"category_scores_gemma":[0.006937088,0.0002549561,0.0008217738,0.0101588,0.0002412321,0.000370411,0.000937592,0.00046179,0.0004085119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01500572,"about_ca_system_score_gemma":0.03038406,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9863413,"about_ca_topic_score_gemma":0.984674,"domain_scores_codex":[0.9987947,0.000174138,0.00008609062,0.0002333071,0.0004065453,0.0003052894],"domain_scores_gemma":[0.9968965,0.0003002587,0.0003848265,0.000190006,0.001939092,0.0002892852],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000278974,0.00004827339,0.8799246,0.0005447465,0.0004531608,0.0003378972,0.001209094,0.01043286,0.002191725,0.002520177,0.0184337,0.08362483],"study_design_scores_gemma":[0.00002154158,0.00004222385,0.9436762,0.00024955,0.0002222967,0.0001783683,0.001653438,0.01783137,0.0009217661,0.0005188031,0.03464641,0.00003795078],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.615081,0.004161736,0.02065492,0.001691773,0.00009903164,0.0006355384,0.3402662,0.001225602,0.01618419],"genre_scores_gemma":[0.8553839,0.001792013,0.03438053,0.0001244174,0.00002209719,0.0001784208,0.106256,0.0001162226,0.001746317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01500572,"threshold_uncertainty_score":0.1088746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06540008105831588,"score_gpt":0.3258907923557295,"score_spread":0.2604907112974136,"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."}}