{"id":"W3036210363","doi":"10.1099/jgv.0.001458","title":"Insights into SARS-CoV-2, the Coronavirus Underlying COVID-19: Recent Genomic Data and the Development of Reverse Genetics Systems","year":2020,"lang":"en","type":"article","venue":"Journal of General Virology","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Fundação de Amparo à Ciência e Tecnologia do Estado de Pernambuco; Conselho Nacional de Desenvolvimento Científico e Tecnológico; International Development Research Centre","keywords":"Biology; Coronavirus; Virology; Genome; Pandemic; Reverse genetics; Genetics; Population; Coronavirus disease 2019 (COVID-19); Disease; Computational biology; Infectious disease (medical specialty); Gene; Medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001295954,0.0001766089,0.0005974757,0.0001102053,0.0002087488,0.00003179431,0.0007510091,0.0001317049,0.000004982725],"category_scores_gemma":[0.0005663492,0.0000948021,0.00007578436,0.0002013384,0.0004699542,0.00006704809,0.0005433554,0.0005303473,0.000007677866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001898148,"about_ca_system_score_gemma":0.001512068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001874001,"about_ca_topic_score_gemma":0.0001610025,"domain_scores_codex":[0.9975373,0.0005103588,0.0009517516,0.0002652378,0.0004856216,0.0002497937],"domain_scores_gemma":[0.9983405,0.0003393116,0.000531316,0.0004862885,0.0001920152,0.0001105182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003555247,0.00007471259,0.004787253,0.0002028395,0.0005292767,0.0001410375,0.005650807,0.00007491469,0.9760523,0.0002953903,0.002893706,0.005742443],"study_design_scores_gemma":[0.008873218,0.0008844102,0.004825754,0.00004385613,0.0003071688,0.0006443922,0.001426408,0.01162861,0.03280646,0.0004714575,0.9378839,0.0002043293],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9707723,0.01502752,0.002821597,0.01058447,0.0002827381,0.0004165564,0.000004245729,0.000006883173,0.00008367166],"genre_scores_gemma":[0.8941355,0.0008979294,0.001435708,0.1030798,0.0004117139,0.000006915665,0.000003754778,0.00002342231,0.000005257921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9432459,"threshold_uncertainty_score":0.3865917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2370783514596827,"score_gpt":0.4130702975109495,"score_spread":0.1759919460512668,"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."}}