{"id":"W4252502640","doi":"10.26434/chemrxiv.12323615.v1","title":"In Silico Investigation of Spice Molecules as Potent Inhibitor of SARS-CoV-2","year":2020,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"In silico; Coronavirus; Docking (animal); ADME; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Small molecule; Piperine; Protease; Viral replication; Virology; Virtual screening; Computational biology; Chemistry; Virus; Biology; Pharmacology; Drug discovery; Coronavirus disease 2019 (COVID-19); Medicine; Infectious disease (medical specialty); Biochemistry; Drug; Enzyme; Disease; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005373906,0.001433419,0.002080541,0.0008637239,0.0005490907,0.001042458,0.001110348,0.001051361,0.005972435],"category_scores_gemma":[0.001019564,0.0004938605,0.001667973,0.0008111676,0.0003600684,0.0005507423,0.0006022666,0.0006719048,0.0005894121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004251541,"about_ca_system_score_gemma":0.0008734946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005514434,"about_ca_topic_score_gemma":0.005965345,"domain_scores_codex":[0.9997817,0.0000738538,0.00001042348,0.0000359628,0.00004639804,0.00005174525],"domain_scores_gemma":[0.9995803,0.0002852619,0.00003662568,0.00001627958,0.00004722493,0.00003437561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005744592,0.0002969469,0.003785768,0.0005944834,0.0003636139,0.0004051949,0.00002706837,0.9816731,0.004910783,0.001591853,0.001569121,0.004207499],"study_design_scores_gemma":[0.0001488047,0.0004870757,0.0006896098,0.00003026365,0.000150458,0.00006812054,0.00004576704,0.9946595,0.001886565,0.0006812321,0.001136061,0.0000164169],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9539996,0.00558878,0.01737814,0.001034868,0.0001923107,0.0001868555,0.003928229,0.0006418702,0.01704943],"genre_scores_gemma":[0.977411,0.002188487,0.01362531,0.000340405,0.00003614134,0.0001924967,0.003405604,0.00008828031,0.002712381],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005972435,"threshold_uncertainty_score":0.01997983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06351602992760479,"score_gpt":0.3313299743195207,"score_spread":0.2678139443919159,"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."}}