{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001052945,0.00009278712,0.0001127105,0.00003348028,0.00004607682,0.000005970564,0.0001103987,0.00007712292,0.00000748747],"category_scores_gemma":[0.00005268156,0.0000593118,0.00003824912,0.0000576668,0.0002160173,0.000001906715,0.00002072105,0.0001028392,0.000001596252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000001343569,"about_ca_system_score_gemma":0.00008457078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004869582,"about_ca_topic_score_gemma":0.000008402528,"domain_scores_codex":[0.999504,0.0000254158,0.0001340162,0.0001786274,0.00004824543,0.0001096662],"domain_scores_gemma":[0.9996123,0.0000132454,0.0000768435,0.0001425628,0.0001308577,0.0000241355],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003852572,0.00003773767,0.0002421235,0.000007900289,0.00004417802,1.064064e-7,0.00001506952,0.01484092,0.9818944,0.002310672,0.00002051043,0.0005477911],"study_design_scores_gemma":[0.0004666255,0.0001061399,0.00260261,0.000007869292,0.00003750243,0.00002845696,0.00001048179,0.02935767,0.9637747,0.000432992,0.003017496,0.0001574806],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9662469,0.00006751063,0.03289701,0.0004432461,0.0001056563,0.0001122592,0.00004538089,0.00001246415,0.00006957974],"genre_scores_gemma":[0.9818406,0.000003030334,0.0175286,0.0002267185,0.0001824635,0.00001412598,0.0001793292,0.000008986549,0.00001615957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01811979,"threshold_uncertainty_score":0.2418665,"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."}}