{"id":"W4281782212","doi":"10.2174/2215083808666220602115932","title":"Screening of Natural Antivirals Against the COVID-19 Pandemic- ACompilation of Updates","year":2022,"lang":"en","type":"article","venue":"Current Traditional Medicine","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Coronavirus; Pandemic; Protease; Medicine; Traditional medicine; Biology; Pharmacology; Coronavirus disease 2019 (COVID-19); Virology; Infectious disease (medical specialty); Disease; Enzyme","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":[0.001031899,0.0001428705,0.0003755288,0.0002849191,0.0002102063,0.000003271562,0.0002479541,0.00002953007,0.0001742902],"category_scores_gemma":[0.000638472,0.00009596774,0.0001248062,0.0005693237,0.0005272417,0.00007274702,0.00007736087,0.0005626293,0.000002329253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001320433,"about_ca_system_score_gemma":0.0003383031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000281743,"about_ca_topic_score_gemma":0.000001810083,"domain_scores_codex":[0.9976167,0.0001805985,0.0004989171,0.0002367418,0.001259175,0.0002078833],"domain_scores_gemma":[0.9984738,0.0008624723,0.0002231427,0.0002405268,0.0001408157,0.00005921408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002036844,0.001154932,0.5271238,0.001243286,0.0004158728,0.00004575602,0.002543299,0.0001289697,0.3446365,0.01376825,0.04302769,0.06387479],"study_design_scores_gemma":[0.01682486,0.002299128,0.2586724,0.0009969646,0.0004947449,0.000532363,0.002675432,0.008167714,0.02112419,0.008924045,0.6787255,0.0005625279],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826616,0.007262094,0.001504617,0.006111233,0.0007028199,0.0006297041,0.0002595445,0.00005420519,0.0008141959],"genre_scores_gemma":[0.9842391,0.00004252415,0.00004621362,0.01467177,0.0004708657,0.00005795533,0.0004501796,0.00001341107,0.000007972243],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6356979,"threshold_uncertainty_score":0.3913451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2314588675272113,"score_gpt":0.4092233414525293,"score_spread":0.1777644739253179,"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."}}