{"id":"W2161212683","doi":"10.1186/1756-0500-3-125","title":"Thermodynamic analysis of regulation in metabolic networks using constraint-based modeling","year":2010,"lang":"en","type":"article","venue":"BMC Research Notes","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Office of Science; U.S. Department of Energy","keywords":"Geobacter sulfurreducens; Metabolic network; Geobacter; Bottleneck; Computational biology; Chemistry; Biological system; Biochemical engineering; Biology; Computer science; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001159513,0.00007669251,0.0001631098,0.0004033125,0.00003937312,0.00001413217,0.000110532,0.0001315854,0.00001441821],"category_scores_gemma":[0.0004373127,0.00007135846,0.00008719594,0.0007869403,0.00009545161,0.000003390921,0.00003282637,0.0001947936,3.235958e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006343786,"about_ca_system_score_gemma":0.00008512162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00044117,"about_ca_topic_score_gemma":0.000851409,"domain_scores_codex":[0.999094,0.0001144535,0.0001932592,0.0002401605,0.0001431073,0.0002149831],"domain_scores_gemma":[0.9994205,0.00002333929,0.00003720067,0.0003071894,0.0001766361,0.00003515594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001908947,0.00001582349,0.002713177,0.000005705694,0.00003018656,6.442236e-8,0.000005412292,0.4280013,0.5684657,0.00008267965,3.836997e-7,0.0006605528],"study_design_scores_gemma":[0.0001312503,0.00001229908,0.008784277,0.000006675151,0.0000385403,6.066064e-7,0.000009727869,0.8253053,0.1656063,0.00001886522,0.00002325411,0.00006287447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8222918,0.0002690426,0.177238,0.0000119585,0.0000659607,0.0000963416,0.00000516981,0.000004855448,0.00001689788],"genre_scores_gemma":[0.9939638,0.00002967706,0.005747967,0.000003263236,0.0001605827,0.000005070021,0.00007014411,0.00001063585,0.000008883233],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4028594,"threshold_uncertainty_score":0.2909914,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06515395749678567,"score_gpt":0.3541919200227975,"score_spread":0.2890379625260119,"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."}}