{"id":"W3203096218","doi":"10.1101/2021.04.02.438287","title":"First-principles model of optimal translation factors stoichiometry","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Searle Scholars Program; Howard Hughes Medical Institute; National Institutes of Health; National Science Foundation","keywords":"Translation (biology); Maximization; Expression (computer science); Proteome; Hierarchy; Stoichiometry; Path (computing); Ribosome; Biological system; Computer science; Computational biology; Biology; Messenger RNA; Chemistry; Bioinformatics; Mathematics; Mathematical optimization; RNA; Genetics; 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":[0.0006937641,0.0007730883,0.001011367,0.0005065232,0.000501961,0.001136251,0.001256881,0.001525159,0.001815441],"category_scores_gemma":[0.00129423,0.0004907013,0.0007057176,0.0003877028,0.001283173,0.001072217,0.0005872857,0.0008586191,0.0005602177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001431926,"about_ca_system_score_gemma":0.0008719101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002718271,"about_ca_topic_score_gemma":0.0010884,"domain_scores_codex":[0.9997252,0.00006008286,0.000008542473,0.00005005825,0.000117346,0.00003866019],"domain_scores_gemma":[0.9997031,0.0001491688,0.00003645867,0.00002873948,0.00005366744,0.00002883271],"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":[0.00003630881,0.00004593209,0.000294014,0.00007435647,0.00001660868,0.0001091293,0.00006131593,0.8441007,0.01387598,0.1380001,0.0006815178,0.002704057],"study_design_scores_gemma":[0.00001273657,0.000009168431,0.00007193472,0.000003283763,0.000002722574,0.00001372204,0.000007174312,0.9688078,0.0007573893,0.02997826,0.0003290894,0.000006743604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2111553,0.000755372,0.7429923,0.002208376,0.0001111213,0.0001474771,0.0005103078,0.0004478652,0.04167188],"genre_scores_gemma":[0.9210848,0.0006482033,0.05834563,0.0003863666,0.00005846422,0.0005040975,0.0001464965,0.000175462,0.01865065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002718271,"threshold_uncertainty_score":0.01038939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03051026115996918,"score_gpt":0.2275165190999253,"score_spread":0.1970062579399561,"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."}}