{"id":"W4281938342","doi":"10.1101/2022.06.07.493653","title":"COVID-MVP: an interactive visualization for tracking SARS-CoV-2 mutations, variants, and prevalence, enabled by curated functional annotations and portable genomics workflow","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; University of British Columbia; University of Calgary; Simon Fraser University","funders":"Genome Canada","keywords":"Workflow; Visualization; Genomics; Coronavirus disease 2019 (COVID-19); Genome; Computational biology; Computer science; Scalability; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Pandemic; Biology; Data science; Genetics; Database; Data mining; Medicine; Gene; Infectious disease (medical specialty); Disease","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":[0.00209228,0.002626479,0.001117175,0.003503896,0.0008590242,0.002653329,0.002159366,0.001358247,0.03725147],"category_scores_gemma":[0.004479115,0.0008537727,0.001745631,0.00166845,0.0003903913,0.002575999,0.004801415,0.002243908,0.01107509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009798183,"about_ca_system_score_gemma":0.001636252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009915135,"about_ca_topic_score_gemma":0.00955976,"domain_scores_codex":[0.9992164,0.0001192295,0.0000665812,0.0002142457,0.0002743371,0.0001091979],"domain_scores_gemma":[0.9982017,0.0006687084,0.0001247131,0.0003172105,0.0004291007,0.000258505],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001784098,0.0001728701,0.006586378,0.001952736,0.0003117838,0.0008118154,0.0008676004,0.007403134,0.01745175,0.006473397,0.8611029,0.09508152],"study_design_scores_gemma":[0.0008400995,0.0002297705,0.014055,0.001046128,0.0002344704,0.0009727199,0.0004749823,0.1730937,0.03659002,0.02737921,0.7444947,0.0005892029],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01078814,0.00107077,0.1368176,0.001583339,0.0006152168,0.0003901913,0.1875384,0.6497452,0.01145108],"genre_scores_gemma":[0.1216083,0.002054524,0.3466913,0.002266804,0.0003718676,0.001405452,0.4174159,0.09608128,0.01210452],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.03725147,"threshold_uncertainty_score":0.1246186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04019156146127083,"score_gpt":0.3257935978340098,"score_spread":0.285602036372739,"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."}}