{"id":"W3112645428","doi":"10.1016/j.gene.2020.145368","title":"Recognition of plausible therapeutic agents to combat COVID-19: An omics data based combined approach","year":2020,"lang":"en","type":"article","venue":"Gene","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Ministerio de Ciencia y Tecnología","keywords":"Biology; Gene; Coronavirus; Genome; In silico; Computational biology; Virology; Gene silencing; Drug repositioning; RNA polymerase; Genetics; RNA; Bioinformatics; Coronavirus disease 2019 (COVID-19); Disease; Drug; Infectious disease (medical specialty); Pharmacology; Medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0004054627,0.0001429615,0.0003068389,0.0001211147,0.00006432289,0.00002285315,0.0004538826,0.00009211897,0.0001130209],"category_scores_gemma":[0.0004105237,0.0001331525,0.00004779543,0.0004833109,0.00005523944,0.00008782336,0.0001808245,0.0001654351,0.00008705968],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007533513,"about_ca_system_score_gemma":0.0007391561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001451298,"about_ca_topic_score_gemma":0.00001242262,"domain_scores_codex":[0.9984403,0.0001088435,0.0002642019,0.0004778562,0.0004419892,0.000266788],"domain_scores_gemma":[0.9987233,0.00007813079,0.00006234003,0.0007116648,0.0001059377,0.0003185978],"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":[0.006233643,0.001750961,0.02433335,0.001140462,0.0002705814,0.00007003094,0.001386859,0.00009680838,0.9354874,0.00005013382,0.007970705,0.02120899],"study_design_scores_gemma":[0.01368403,0.003593302,0.004770929,0.00005165828,0.0003095492,0.00002306057,0.0006164021,0.1937865,0.697073,0.0002652613,0.08530185,0.000524482],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9648055,0.0001552366,0.02762756,0.004369115,0.00008160391,0.00135757,0.0004494807,0.0001353344,0.001018612],"genre_scores_gemma":[0.7223096,0.000003644913,0.005408049,0.2712117,0.0001135424,0.00003189364,0.0008813788,0.00003312882,0.000007038634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2668426,"threshold_uncertainty_score":0.5429802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.318614544717861,"score_gpt":0.4082047664072634,"score_spread":0.0895902216894024,"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."}}