{"id":"W1922871238","doi":"10.1002/biot.201400522","title":"Constructing kinetic models of metabolism at genome‐scales: A review","year":2015,"lang":"en","type":"review","venue":"Biotechnology Journal","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Toronto","keywords":"In silico; Identifiability; Computer science; Constraint (computer-aided design); Biological system; Computational biology; Systems biology; Biochemical engineering; Biology; Mathematics; Machine learning; Genetics","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":[0.0007278312,0.001587584,0.001797868,0.002384505,0.0003080924,0.001182775,0.001664909,0.001378992,0.002685461],"category_scores_gemma":[0.001114546,0.0007227547,0.0009187282,0.00342739,0.000713781,0.002313688,0.0007349668,0.001456723,0.002414997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008775669,"about_ca_system_score_gemma":0.001254448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001950618,"about_ca_topic_score_gemma":0.001784937,"domain_scores_codex":[0.9998249,0.00002941703,0.00002483871,0.00004529905,0.00006283377,0.00001272478],"domain_scores_gemma":[0.9993985,0.0003953679,0.00006574064,0.00002510304,0.00009204939,0.00002314328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004129672,0.0001077397,0.0003419238,0.02956304,0.0001910541,0.0002636461,0.0001073225,0.01476463,0.003645838,0.05496195,0.02022602,0.8757856],"study_design_scores_gemma":[0.00001080353,0.00009239731,0.0005737137,0.003876499,0.0001717956,0.0009136572,0.00007476343,0.004894868,0.002094922,0.02196894,0.9652492,0.00007845997],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003604406,0.9883654,0.008233982,0.0003251169,0.0001812241,0.00001237075,0.00008112737,0.00004665649,0.002393682],"genre_scores_gemma":[0.001707303,0.9937264,0.003801434,0.00007797094,0.00009836084,0.00001502963,0.00008120974,0.000008406979,0.0004839177],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002685461,"threshold_uncertainty_score":0.008983731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02831267351615296,"score_gpt":0.2817667364239478,"score_spread":0.2534540629077949,"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."}}