{"id":"W2033872945","doi":"10.1021/sb400142b","title":"Universal Genetic Assay for Engineering Extracellular Protein Expression","year":2013,"lang":"en","type":"article","venue":"ACS Synthetic Biology","topic":"Bacterial Genetics and Biotechnology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Great Lakes Bioenergy Research Center; National Institute of Food and Agriculture; Petroleum Technology Research Centre; U.S. Department of Energy","keywords":"Secretion; Synthetic biology; Escherichia coli; Secretory protein; Protein engineering; Metabolic engineering; Biology; Extracellular; Fusion protein; Computational biology; Green fluorescent protein; Recombinant DNA; High-throughput screening; Directed evolution; Secretory pathway; Cell biology; Biochemistry; Cell; Gene; Enzyme; Mutant","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001373862,0.0002234781,0.0002011642,0.0000676463,0.00007081227,0.00002228246,0.0003345559,0.0006345466,0.00008192423],"category_scores_gemma":[0.0001397278,0.0001976006,0.00009059184,0.00005961933,0.0001300718,0.000003102143,0.0001784661,0.0001084665,0.00003994506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001275983,"about_ca_system_score_gemma":0.00003862615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002060321,"about_ca_topic_score_gemma":0.000002850416,"domain_scores_codex":[0.9987123,0.00006269036,0.0002395073,0.0004970259,0.00004497604,0.0004435254],"domain_scores_gemma":[0.9992573,0.00002516617,0.00008775816,0.0004555514,0.0000884215,0.00008577367],"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":[0.00002324014,0.00003559686,0.00008796759,0.00001581711,0.0000261817,7.768091e-7,0.000006319427,0.00001394885,0.9891635,0.0006168743,0.0002938044,0.009715964],"study_design_scores_gemma":[0.0003638907,0.000458628,0.0001874575,0.00001507218,0.00001279799,0.00001665933,0.00001605074,0.0002584874,0.8840824,0.0004944684,0.1138385,0.0002556282],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.958609,0.0008808592,0.03875072,0.0004974009,0.0002887376,0.0008122871,0.00002490463,0.00004472961,0.00009139966],"genre_scores_gemma":[0.9815036,0.00006929183,0.0171732,0.0000535793,0.000250332,0.000247242,0.00008493674,0.00003977971,0.0005780091],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1135447,"threshold_uncertainty_score":0.8057918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005753903352248145,"score_gpt":0.195402883787181,"score_spread":0.1896489804349329,"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."}}