{"id":"W4392766463","doi":"10.1098/rsif.2023.0652","title":"Optimal control of ribosome population for gene expression under periodic nutrient intake","year":2024,"lang":"en","type":"article","venue":"Journal of The Royal Society Interface","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Institut Universitaire de France; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche","keywords":"Ribosome; Ribosome biogenesis; Population; Translation (biology); Protein biosynthesis; Biology; Control theory (sociology); Biological system; Messenger RNA; Computer science; Genetics; Control (management); Gene; RNA; Artificial intelligence","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":[0.0004910064,0.0003587031,0.0005531394,0.0003627604,0.0003422187,0.00100048,0.0003867801,0.0006131579,0.001190282],"category_scores_gemma":[0.002254338,0.00028917,0.0004290389,0.0002022318,0.001250851,0.0005941424,0.0005637471,0.0004487697,0.0001489816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001097398,"about_ca_system_score_gemma":0.0009948702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002186394,"about_ca_topic_score_gemma":0.001554704,"domain_scores_codex":[0.9998747,0.00002897788,0.000004940068,0.00003832748,0.00002190229,0.00003109382],"domain_scores_gemma":[0.9994807,0.000276602,0.0001272303,0.0000242294,0.00004381649,0.00004737837],"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":[0.000196812,0.0001058115,0.001543968,0.0001616747,0.00004954456,0.000231145,0.000183264,0.7794523,0.1348119,0.07563657,0.0008181043,0.006808891],"study_design_scores_gemma":[0.0000224895,0.00003727729,0.0004937545,0.000009085226,0.00001102945,0.00001807983,0.00004043568,0.9853231,0.00410241,0.009616094,0.0003097987,0.00001657103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7603545,0.0005197868,0.2267271,0.001134798,0.00008752877,0.00004957199,0.0001065194,0.0001604983,0.01085961],"genre_scores_gemma":[0.9909574,0.0001918485,0.007279921,0.00006189357,0.00001270699,0.00006482978,0.00002548824,0.00003126898,0.0013747],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002186394,"threshold_uncertainty_score":0.007962227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00914460264260092,"score_gpt":0.2543204393420556,"score_spread":0.2451758366994546,"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."}}