{"id":"W7028449248","doi":"","title":"Extraction of elementary rate constants from global network analysis of E.coli central metabolism","year":2008,"lang":"en","type":"article","venue":"NPARC","topic":"Civil and Structural Engineering Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Extraction (chemistry); Network analysis; Global network; Metabolism; Component (thermodynamics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0006233408,0.0006695157,0.0008033227,0.001926058,0.0002917386,0.0008547396,0.0005436347,0.0005791652,0.004793008],"category_scores_gemma":[0.005175822,0.0003931565,0.0007181629,0.001445543,0.0001326128,0.0008084926,0.0002639568,0.0004704556,0.002669122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000502673,"about_ca_system_score_gemma":0.000734296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002422607,"about_ca_topic_score_gemma":0.002583536,"domain_scores_codex":[0.9997817,0.00004206875,0.00001770464,0.00008053713,0.00005720624,0.00002076375],"domain_scores_gemma":[0.9982517,0.0008021671,0.0001727903,0.0001782405,0.0005289878,0.00006608317],"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":[0.001903421,0.000240461,0.06289494,0.002452315,0.0006752174,0.000508224,0.0002616002,0.124602,0.5048108,0.005075763,0.01137521,0.2852],"study_design_scores_gemma":[0.00008496862,0.0003589571,0.1271861,0.0001390231,0.0004790252,0.0005389265,0.0002522276,0.5815078,0.262224,0.01075364,0.01630642,0.000168915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7492954,0.001471599,0.2157977,0.0005577136,0.0001647347,0.0002269955,0.02066744,0.003948407,0.007870004],"genre_scores_gemma":[0.9038111,0.0011178,0.06824292,0.000047817,0.0000372195,0.0001642519,0.02089426,0.0004720003,0.005212705],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004793008,"threshold_uncertainty_score":0.01603425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01101773617733426,"score_gpt":0.2377263792910114,"score_spread":0.2267086431136772,"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."}}