{"id":"W4411122517","doi":"10.1016/j.synbio.2025.06.003","title":"Metabolic engineering of Escherichia coli for squalene overproduction","year":2025,"lang":"en","type":"article","venue":"Synthetic and Systems Biotechnology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; Key Technologies Research and Development Program; Science and Technology Commission of Shanghai Municipality; Shanghai Tobacco Group; Canadian Anesthesiologists' Society","keywords":"Overproduction; Squalene; Metabolic engineering; Metabolic regulation; Biotechnology; Chemistry; Mathematics; Biology; Biochemistry; Metabolism","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002423453,0.0004996808,0.0002883933,0.000297197,0.0001296798,0.0005103749,0.0002898888,0.0002634404,0.0004995891],"category_scores_gemma":[0.0001836632,0.000166226,0.0003161522,0.0004099135,0.0001751995,0.0002027193,0.0004932652,0.0005479912,0.0004904357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003904547,"about_ca_system_score_gemma":0.0003740544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00112574,"about_ca_topic_score_gemma":0.001455474,"domain_scores_codex":[0.9997634,0.00004662376,0.00002596726,0.00003919665,0.00008129157,0.00004347897],"domain_scores_gemma":[0.9999251,0.00001349642,0.00001972754,0.00001063748,0.0000169155,0.00001414723],"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":[0.0000309799,0.00004553139,0.0001803429,0.00003595813,0.000006053664,0.00005302011,0.00001329658,0.000324581,0.9971297,0.0002431313,0.00003691942,0.001900327],"study_design_scores_gemma":[0.000006307757,0.0001048826,0.0005956179,0.000007624836,0.00001297027,0.00008562109,0.00002854514,0.002407266,0.9938315,0.00005895493,0.002853402,0.000007377575],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9556468,0.0007773754,0.03826776,0.0003368789,0.00008252035,0.0001893225,0.001013832,0.000396552,0.003289067],"genre_scores_gemma":[0.9665257,0.0008253923,0.02847839,0.00005986962,0.000008167414,0.00007852028,0.001113739,0.00008480227,0.002825441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00112574,"threshold_uncertainty_score":0.002832949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004578994065085165,"score_gpt":0.2088123520250259,"score_spread":0.2042333579599407,"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."}}