{"id":"W2894552244","doi":"10.1103/physreve.101.022118","title":"Optimal control of protein copy number","year":2020,"lang":"en","type":"article","venue":"Physical review. E","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Waterloo","funders":"Simon Fraser University; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Receptor; Optogenetics; Chemical biology; Cytosol; Cell membrane; Cell; Extracellular; Biophysics; Chemistry; Cell biology; Biology; Biochemistry; Neuroscience","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":[0.0006852098,0.0005057216,0.0004905667,0.0004292277,0.0003457433,0.001008935,0.0008348548,0.0005140104,0.001640199],"category_scores_gemma":[0.003850016,0.0003837433,0.0002664403,0.0003234078,0.001416203,0.001103993,0.0007276624,0.0006535003,0.0002630798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001833039,"about_ca_system_score_gemma":0.001020199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001457634,"about_ca_topic_score_gemma":0.001197686,"domain_scores_codex":[0.9997434,0.00006668019,0.000008911472,0.00008706396,0.00005025381,0.00004357985],"domain_scores_gemma":[0.9990519,0.0006164063,0.0001430189,0.00005862534,0.00007121695,0.00005880138],"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":[0.0001073939,0.00007445704,0.000480953,0.0001013758,0.00002729718,0.00006164117,0.00009822089,0.6376466,0.04426916,0.2987548,0.001092982,0.01728525],"study_design_scores_gemma":[0.00001863332,0.00003262586,0.0002127934,0.000006897978,0.000005603066,0.00001144868,0.00001630426,0.9343817,0.004219427,0.06032904,0.0007519776,0.0000136071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2225055,0.0006246674,0.7534828,0.0011739,0.0001116335,0.00006728009,0.000155423,0.0003154906,0.02156334],"genre_scores_gemma":[0.9715768,0.0003434455,0.02418766,0.00006312963,0.00001793958,0.00008642452,0.00003704361,0.00005997927,0.003627746],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001833039,"threshold_uncertainty_score":0.01329964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009202534886924829,"score_gpt":0.2861107750415008,"score_spread":0.2769082401545759,"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."}}