{"id":"W3025569057","doi":"10.4103/ijmr.ijmr_1253_20","title":"Mapping the genomic landscape &amp; diversity of COVID-19 based on &gt;3950 clinical isolates of SARS-CoV-2","year":2020,"lang":"en","type":"article","venue":"The Indian Journal of Medical Research","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Population; Genetic diversity; Demography; Timeline; Transmissibility (structural dynamics); Geography; Outbreak; Transmission (telecommunications); Biology; Evolutionary biology; Virology; Infectious disease (medical specialty); Disease; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002933063,0.0002814742,0.0003597519,0.001597046,0.000515788,0.000738563,0.0002363156,0.0003652472,0.001205373],"category_scores_gemma":[0.000743632,0.0001827957,0.000513883,0.001942367,0.0003959485,0.0002456183,0.0004603522,0.0005393642,0.0006448467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004041523,"about_ca_system_score_gemma":0.0002474572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004103332,"about_ca_topic_score_gemma":0.004760727,"domain_scores_codex":[0.9996159,0.00005280722,0.00003111146,0.0001326634,0.00007689137,0.00009060225],"domain_scores_gemma":[0.9995932,0.00006833405,0.00009402369,0.00004758304,0.00008067022,0.0001161642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001321157,0.0002486257,0.5537347,0.0001917826,0.0002464669,0.001029045,0.001828723,0.0007953993,0.4200476,0.0004382207,0.001501747,0.01861656],"study_design_scores_gemma":[0.0000130772,0.000252264,0.9884437,0.00002155662,0.00003665149,0.0009736449,0.0005839859,0.0009905898,0.00440397,0.0001005938,0.004168809,0.00001126554],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955578,0.0002861853,0.0005274431,0.00005319214,0.000007232161,0.00002847173,0.002728841,0.000009633143,0.0008010734],"genre_scores_gemma":[0.9867228,0.0002361955,0.001699816,0.0001376018,0.00001442608,0.00002396305,0.01070456,0.00001874231,0.0004417501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004103332,"threshold_uncertainty_score":0.008158922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3065202466367425,"score_gpt":0.4706900965514757,"score_spread":0.1641698499147332,"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."}}