{"id":"W1983966050","doi":"10.1371/journal.pcbi.1000887","title":"Characterizing the Metabolism of Dehalococcoides with a Constraint-Based Model","year":2010,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Strategic Environmental Research and Development Program; University of Toronto; Ontario Genomics Institute; Ontario Genomics; Genome Canada; U.S. Department of Defense; U.S. Department of Energy; Government of Canada","keywords":"Dehalococcoides; Genome; Biology; Gene; Computational biology; Metabolic network; Genetics; Metabolic engineering; Metabolic pathway; Chemistry","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":[0.0001327554,0.000728804,0.0005281093,0.000217754,0.0002739877,0.0005759315,0.0005915527,0.0005993673,0.0009909109],"category_scores_gemma":[0.0005059417,0.0002215805,0.0006953352,0.0004437873,0.0002488704,0.0004756042,0.0003985936,0.0004759611,0.0001448591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008728091,"about_ca_system_score_gemma":0.0007863917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01474113,"about_ca_topic_score_gemma":0.008563009,"domain_scores_codex":[0.9999286,0.00001547189,0.00000387603,0.00002895573,0.00001144803,0.00001157461],"domain_scores_gemma":[0.9998362,0.00008117562,0.00002745731,0.00001671579,0.00002066179,0.0000178705],"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":[0.00007399888,0.00003315477,0.001339982,0.00005798116,0.0000246921,0.00006682042,0.00001362262,0.9809601,0.01330026,0.002565094,0.00008500705,0.001479343],"study_design_scores_gemma":[0.00001444657,0.00002908052,0.0005209464,0.000001561021,0.000009866718,0.00001294045,0.000007875148,0.9965671,0.001337735,0.001121044,0.0003728394,0.000004550611],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.869662,0.0005790349,0.1187058,0.0003174717,0.00002462057,0.00008722283,0.002650133,0.0002143613,0.007759451],"genre_scores_gemma":[0.9481636,0.0007479628,0.0467014,0.00005596998,0.00001091482,0.0002205021,0.002209099,0.00005686775,0.001833613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01474113,"threshold_uncertainty_score":0.02931064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00831175843949795,"score_gpt":0.2158167671792403,"score_spread":0.2075050087397423,"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."}}