{"id":"W2041540935","doi":"10.1007/s00253-013-5361-4","title":"Metabolic pathway optimization using ribosome binding site variants and combinatorial gene assembly","year":2013,"lang":"en","type":"article","venue":"Applied Microbiology and Biotechnology","topic":"Plant biochemistry and biosynthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":105,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Directorate for Biological Sciences; Petroleum Technology Research Centre; Lawrence Berkeley National Laboratory; Biological and Environmental Research; National Science Foundation","keywords":"Mevalonate pathway; Farnesyl pyrophosphate; Biochemistry; Biology; Gene; Metabolic pathway; Translational efficiency; Metabolic engineering; Operon; Isopentenyl pyrophosphate; Computational biology; Biosynthesis; Translation (biology); Escherichia coli; Messenger RNA","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":[0.00014602,0.0002638368,0.0002988894,0.0001000667,0.0002031517,0.000030589,0.0001594918,0.001218687,0.00002052977],"category_scores_gemma":[0.00003508626,0.0002379776,0.00003647378,0.0001265384,0.0003729272,0.000007606412,0.0002850246,0.0001836182,0.00001760569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007863982,"about_ca_system_score_gemma":0.00003301745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001855947,"about_ca_topic_score_gemma":0.000002740423,"domain_scores_codex":[0.9987029,0.00004332832,0.0002335205,0.0006063631,0.00002660493,0.0003872789],"domain_scores_gemma":[0.9994933,0.00002178353,0.0001285807,0.0002515659,0.00003513146,0.00006962675],"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":[0.00004923442,0.00004039878,0.0002297748,0.00001199075,0.00008500362,0.000002721397,0.000008562766,0.000009303603,0.9979366,0.0004335363,0.0001051535,0.001087738],"study_design_scores_gemma":[0.0006391208,0.00008301541,0.0001200039,0.000006464878,0.00004105777,0.0003912341,0.00002551243,0.0001632126,0.9943261,0.00008150122,0.003820303,0.0003024595],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969479,0.001032082,0.001040565,0.0002373069,0.0001985573,0.0002727803,0.0001408702,0.00004824946,0.00008168434],"genre_scores_gemma":[0.9935579,0.0008818959,0.0046142,0.0001980038,0.000123096,0.00002231693,0.0005379128,0.0000187844,0.00004586718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00371515,"threshold_uncertainty_score":0.9704444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005562153533055654,"score_gpt":0.1851450243881091,"score_spread":0.1795828708550535,"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."}}