{"id":"W2038624513","doi":"10.1016/j.ymben.2011.09.009","title":"Identification of bottlenecks in Escherichia coli engineered for the production of CoQ10","year":2011,"lang":"en","type":"article","venue":"Metabolic Engineering","topic":"Coenzyme Q10 studies and effects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Escherichia coli; Identification (biology); Computational biology; Production (economics); Biotechnology; Biology; Chemistry; Biochemistry; Gene; Economics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004952132,0.000670531,0.0005670465,0.0004855641,0.0003397499,0.0009606398,0.0007147234,0.0004922077,0.0009919669],"category_scores_gemma":[0.001300324,0.0004084603,0.0002834998,0.0005214093,0.0004774876,0.0004820466,0.0005758429,0.0008791764,0.0003483695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00120454,"about_ca_system_score_gemma":0.0008753698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01152743,"about_ca_topic_score_gemma":0.006776988,"domain_scores_codex":[0.9994672,0.00009140242,0.00006028393,0.00009447182,0.0001670093,0.0001196037],"domain_scores_gemma":[0.9990271,0.0003609988,0.0001965165,0.00008435908,0.0001995747,0.0001314101],"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":[0.0001699236,0.0000897781,0.001026197,0.00002771812,0.000006880083,0.00006312066,0.00003543754,0.0001644731,0.9966859,0.000117097,0.00004603925,0.001567347],"study_design_scores_gemma":[0.000009570329,0.0001127994,0.002904774,0.000005340883,0.00001420001,0.0001035096,0.00007244116,0.001425547,0.994926,0.00003780961,0.0003772684,0.00001066166],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949004,0.0001770713,0.003885886,0.0001000265,0.00001469893,0.0000321334,0.0002917058,0.000133418,0.0004646968],"genre_scores_gemma":[0.9942995,0.0002684173,0.003645966,0.00005066088,0.000003956243,0.00003512712,0.000489387,0.0001200261,0.001086882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01152743,"threshold_uncertainty_score":0.02292067,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01036927668954256,"score_gpt":0.2156115893176582,"score_spread":0.2052423126281157,"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."}}