{"id":"W4312039669","doi":"10.1101/2022.12.08.519651","title":"Biochemistry-informed design selects potent siRNAs against SARS-CoV-2","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Clinical Research Institute","funders":"Région Occitanie Pyrénées-Méditerranée","keywords":"RNA interference; Small interfering RNA; Computational biology; Biology; RNA; Computer science; Gene; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005538331,0.0007918661,0.0006067913,0.0003677079,0.0003088044,0.001018965,0.0003555557,0.0005610441,0.002479603],"category_scores_gemma":[0.0003595825,0.0003876178,0.0006083345,0.0002415794,0.0002784907,0.0003313971,0.0004042458,0.0005650311,0.002138846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007140998,"about_ca_system_score_gemma":0.0007812912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004230493,"about_ca_topic_score_gemma":0.0007576001,"domain_scores_codex":[0.9997637,0.00003194497,0.00002342696,0.00005540127,0.00008523089,0.00004032766],"domain_scores_gemma":[0.9999102,0.00001577342,0.00001751251,0.00001746075,0.00002318558,0.00001571642],"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":[0.0001189857,0.00006752506,0.0004100769,0.0002122868,0.00002437516,0.0001389913,0.0000424359,0.01741872,0.9571363,0.003420043,0.0006417417,0.02036846],"study_design_scores_gemma":[0.00004812675,0.0002992486,0.0003606284,0.00001229666,0.00003162095,0.000138426,0.00001787059,0.03309401,0.9493904,0.001194426,0.01538833,0.00002472582],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5643468,0.003373254,0.3938102,0.000580714,0.0002375395,0.001120705,0.00227269,0.004319678,0.02993851],"genre_scores_gemma":[0.7194638,0.002232763,0.2634327,0.0002127164,0.00002376201,0.0004361352,0.002176139,0.000484112,0.01153777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002479603,"threshold_uncertainty_score":0.008295119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02261350299573978,"score_gpt":0.2462524524737264,"score_spread":0.2236389494779867,"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."}}