{"id":"W3110972717","doi":"10.1101/2020.12.16.423118","title":"Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"SARS-CoV-2 and COVID-19 Research","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Research in Immunology and Cancer; Université de Montréal","funders":"Réseau Québécois de Recherche sur les Médicaments","keywords":"Spike (software development); Spike Protein; Infectivity; Flexibility (engineering); Mutation; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Dynamics (music); Occupancy; Protein dynamics; Coronavirus disease 2019 (COVID-19); Computational biology; Biology; Protein structure; Genetics; Virus; Computer science; Gene; Biochemistry; Physics; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006089612,0.0005192931,0.0006361385,0.0004021824,0.0001916446,0.0002282907,0.0002169018,0.0004748471,0.000002464551],"category_scores_gemma":[0.0003296458,0.0005463942,0.0001570822,0.000360229,0.00006686516,0.0002256001,0.00027322,0.0009990591,0.00005858153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005111901,"about_ca_system_score_gemma":0.001177918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001336749,"about_ca_topic_score_gemma":0.00000689622,"domain_scores_codex":[0.9972574,0.00007073393,0.0005960309,0.0008863349,0.0006240974,0.0005653753],"domain_scores_gemma":[0.9980965,0.00007640875,0.000326406,0.0005560938,0.0008236,0.000121032],"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":[0.0008996475,0.0002240504,0.001404648,0.002602903,0.0002995578,0.00004142097,0.00004021965,0.0004578755,0.9894177,0.004539985,0.00005155617,0.00002048777],"study_design_scores_gemma":[0.001280254,0.0002447142,0.001840093,0.0005319024,0.0000755658,6.094104e-8,0.000001444209,0.4675321,0.5251712,0.00004330543,0.002878208,0.0004011599],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.953182,0.0002034631,0.04189853,0.0003523304,0.0002863098,0.00323926,0.000491166,0.0003043911,0.00004255112],"genre_scores_gemma":[0.9920834,0.00003091406,0.00232435,0.00433343,0.0003557038,0.00073253,0.000002397427,0.0001346075,0.000002607101],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4670742,"threshold_uncertainty_score":0.9996988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04242816877322774,"score_gpt":0.2923100060141534,"score_spread":0.2498818372409257,"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."}}