{"id":"W2951608042","doi":"10.1101/330506","title":"A new <i>in vitro</i> assay measuring direct interaction of nonsense suppressors with the eukaryotic protein synthesis machinery","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Orphan Disease Center, Perelman School of Medicine, University of Pennsylvania; Michael Smith Health Research BC; University of Illinois at Urbana-Champaign; National Institutes of Health; PTC Therapeutics; University of Pennsylvania","keywords":"Nonsense; Suppressor; In vitro; Nonsense mutation; Nonsense-mediated decay; Biology; Amino acid; Computational biology; Cell biology; Genetics; Chemistry; Gene; Mutation; RNA","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008233315,0.0009045001,0.0005049187,0.000965725,0.0005220593,0.000899728,0.0006979416,0.0006278791,0.00498655],"category_scores_gemma":[0.000811722,0.0004028128,0.0004706999,0.0004996336,0.0004087638,0.0005286953,0.0005549703,0.001259391,0.002383344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005799214,"about_ca_system_score_gemma":0.0003325367,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005790548,"about_ca_topic_score_gemma":0.0009124954,"domain_scores_codex":[0.9987729,0.000374031,0.000118545,0.0002655952,0.0003762243,0.0000926575],"domain_scores_gemma":[0.9989779,0.0003746172,0.0002058345,0.0001924611,0.0001531575,0.00009612344],"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":[0.00009184469,0.00005550294,0.0007160198,0.00007774609,0.00001029425,0.0000260849,0.00002241867,0.0001154682,0.9953091,0.0002115893,0.0002778484,0.003086119],"study_design_scores_gemma":[0.000003760002,0.00008076348,0.001357526,0.000005499216,0.000009611295,0.00008275643,0.00000993158,0.0004497787,0.9959169,0.00007682187,0.001998167,0.000008420917],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6319382,0.005801383,0.3265227,0.0006915405,0.0006396744,0.0007147891,0.00884714,0.003318211,0.02152638],"genre_scores_gemma":[0.6902476,0.002638793,0.27022,0.0004152913,0.0001822847,0.0007343828,0.01282637,0.0006945664,0.02204084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00498655,"threshold_uncertainty_score":0.01668167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01143799982560484,"score_gpt":0.2054649102984193,"score_spread":0.1940269104728145,"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."}}