{"id":"W4297030705","doi":"10.1016/j.ifacol.2022.09.125","title":"A Dynamic Constraint-based Modelling (DCBM) Approach With Alternative Metabolic Objective Functions Predicts The impact of Oxidative Stress on Stored Red Blood Cells (RBCs)","year":2022,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Flux balance analysis; Metabolic network; Flux (metallurgy); Metabolic flux analysis; Computer science; Constraint (computer-aided design); Metabolic engineering; Biological system; Mathematical optimization; Mathematics; Chemistry; Biology; Biochemistry; Metabolism","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":[0.0006410464,0.00111619,0.0008325328,0.0006120268,0.000370253,0.001236045,0.001029737,0.001358045,0.001356764],"category_scores_gemma":[0.001430719,0.0004930762,0.001197986,0.0006571258,0.000450579,0.0007077887,0.0007386939,0.001048109,0.000219837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008425387,"about_ca_system_score_gemma":0.001139771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01157462,"about_ca_topic_score_gemma":0.00615487,"domain_scores_codex":[0.9997621,0.00008236775,0.00001355609,0.00006248015,0.00005441482,0.00002496548],"domain_scores_gemma":[0.999424,0.0003574401,0.00008372587,0.00003037206,0.00008282527,0.00002162717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008320543,0.00000708105,0.0001678478,0.00002338326,0.00001127959,0.00001410814,0.0000066482,0.9946862,0.0008439018,0.001907205,0.0000790532,0.002244889],"study_design_scores_gemma":[0.000001065584,0.000004127136,0.00004555069,0.000002203659,0.000002995996,0.000002950386,0.000001676862,0.9989204,0.0002134591,0.0006304971,0.0001727545,0.000002267539],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03231254,0.0003218344,0.9629959,0.000230412,0.0000304469,0.00004695961,0.0003844636,0.000187468,0.00348996],"genre_scores_gemma":[0.7689602,0.0007774625,0.2236872,0.0001842198,0.00005644227,0.0005056864,0.0009314765,0.0002073171,0.004689987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01157462,"threshold_uncertainty_score":0.02301449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007932417684997625,"score_gpt":0.2180087866985958,"score_spread":0.2100763690135982,"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."}}