{"id":"W2144337489","doi":"10.1186/1754-6834-6-122","title":"Increasing the metabolic capacity of Escherichia coli for hydrogen production through heterologous expression of the Ralstonia eutropha SH operon","year":2013,"lang":"en","type":"article","venue":"Biotechnology for Biofuels","topic":"Metalloenzymes and iron-sulfur proteins","field":"Energy","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Hydrogenase; Ralstonia; Biochemistry; Escherichia coli; Metabolic engineering; Operon; Cupriavidus necator; Chemistry; NAD+ kinase; Fermentation; Hydrogen production; Enzyme; Biology; Bacteria; Catalysis; Gene","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":[0.0002293536,0.0004782254,0.0002401018,0.0001623757,0.00007454969,0.0003339661,0.0002134162,0.0002215102,0.000639686],"category_scores_gemma":[0.000218784,0.0001047999,0.0002837145,0.0001774811,0.0001910422,0.0001743047,0.0003599078,0.0004310914,0.0003529853],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002483115,"about_ca_system_score_gemma":0.0002225337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005025755,"about_ca_topic_score_gemma":0.0005731794,"domain_scores_codex":[0.9998192,0.00003222447,0.00002263045,0.00002597701,0.00006276274,0.00003711519],"domain_scores_gemma":[0.9998596,0.00003361057,0.0000323531,0.00003398796,0.00002465602,0.00001581884],"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":[0.00002020688,0.00001872181,0.0001676808,0.00002636329,0.0000036898,0.00001803711,0.000007535078,0.00005989066,0.9989601,0.00004252197,0.00001186448,0.0006632552],"study_design_scores_gemma":[0.0000057035,0.0001259812,0.00136116,0.000004655754,0.00001474052,0.0001207549,0.00001679152,0.0006121642,0.9964283,0.00002337632,0.001282549,0.00000385654],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907101,0.0003981428,0.007128405,0.0001487054,0.00001808632,0.00002977614,0.0002947413,0.0001222667,0.001149752],"genre_scores_gemma":[0.986823,0.000470904,0.01036233,0.00004558962,0.000007052191,0.0000293634,0.0008778641,0.00004229999,0.001341517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.000639686,"threshold_uncertainty_score":0.002139926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02407731741184117,"score_gpt":0.2360525965985462,"score_spread":0.211975279186705,"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."}}