{"id":"W4402001164","doi":"10.1128/mbio.00873-24","title":"Diagnosis and mitigation of the systemic impact of genome reduction in <i>Escherichia coli</i> DGF-298","year":2024,"lang":"en","type":"article","venue":"mBio","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Fonds de recherche du Québec – Nature et technologies; Novo Nordisk Fonden; Compute Canada; University of California, San Diego; Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec; Université de Sherbrooke","keywords":"Escherichia coli; Reduction (mathematics); Computational biology; Chemistry; Medicine; Biology; Genetics; Gene; Mathematics","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":[0.0002790765,0.0005467383,0.0004097277,0.0002480962,0.0001526888,0.0005745317,0.0003708494,0.0005120595,0.0004536209],"category_scores_gemma":[0.0004339268,0.0001667928,0.0002792115,0.0002312574,0.0002570101,0.0002295067,0.0003605909,0.0005806988,0.0001698975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004073511,"about_ca_system_score_gemma":0.0003448866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001399844,"about_ca_topic_score_gemma":0.001410081,"domain_scores_codex":[0.9996492,0.00005355687,0.00002171755,0.0001037312,0.0001129654,0.00005889807],"domain_scores_gemma":[0.9997274,0.00005200523,0.00009384584,0.00003938783,0.00005468339,0.00003266217],"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":[0.00006748223,0.00004131788,0.001918697,0.00004436212,0.000006588334,0.00005160387,0.000008971669,0.0007729125,0.994139,0.00007646104,0.00005430671,0.002818414],"study_design_scores_gemma":[0.000005769716,0.0002972288,0.005284418,0.00001099952,0.00002384505,0.000143422,0.0000637685,0.008202951,0.9848999,0.0001004791,0.0009556418,0.00001162901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9824768,0.0003569066,0.0151383,0.0002644546,0.00002982287,0.00005117703,0.0005280133,0.0003005068,0.0008539321],"genre_scores_gemma":[0.9872397,0.0002944164,0.0112959,0.0000958077,0.000005236141,0.00002792599,0.0005693798,0.00004613932,0.0004255096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001399844,"threshold_uncertainty_score":0.002955556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004680264241438208,"score_gpt":0.219876497471523,"score_spread":0.2151962332300848,"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."}}