{"id":"W3021839758","doi":"10.1101/2020.05.01.073262","title":"SARS-CoV-2 is well adapted for humans. What does this mean for re-emergence?","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fusion Genomics (Canada); University of British Columbia","funders":"University of British Columbia; Broad Institute; Compute Canada; Tunghai University","keywords":"Transmission (telecommunications); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Outbreak; Population; Biology; Coronavirus disease 2019 (COVID-19); Pandemic; Virology; Evolutionary biology; Environmental health; Medicine; Computer science; Infectious disease (medical specialty); Disease; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001129244,0.001076345,0.001575333,0.0005531072,0.0003689984,0.0004922568,0.001177434,0.001107102,0.000114902],"category_scores_gemma":[0.0006631927,0.0009624373,0.0008861565,0.0007851857,0.000251906,0.0003931551,0.0006799061,0.001265724,0.0002549689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004431048,"about_ca_system_score_gemma":0.001784787,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000162641,"about_ca_topic_score_gemma":0.00004317118,"domain_scores_codex":[0.9939491,0.0001207818,0.001139535,0.002396456,0.001062119,0.001331997],"domain_scores_gemma":[0.9948577,0.0002654222,0.0005415916,0.002322302,0.001767706,0.0002452781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000953475,0.0002878776,0.001531474,0.003588102,0.0007471504,0.00007794872,0.0001762758,2.543394e-7,0.968617,0.0005260289,0.02346678,0.00002768443],"study_design_scores_gemma":[0.001611437,0.0002825518,0.0003793115,0.0007734676,0.0003673768,1.927124e-8,0.00003869818,0.0007923477,0.6304022,0.00002829227,0.3645921,0.0007321215],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9390514,0.01209337,0.01104538,0.01139358,0.006988397,0.01551258,0.001712546,0.001987626,0.000215126],"genre_scores_gemma":[0.9111981,0.0008491368,0.01204748,0.06840253,0.003195193,0.003582859,0.000003924416,0.000687313,0.00003345588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3411254,"threshold_uncertainty_score":0.9992826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06319866868712981,"score_gpt":0.3247454883264819,"score_spread":0.2615468196393521,"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."}}