{"id":"W2013487313","doi":"10.1371/journal.pcbi.1000472","title":"On the Accessibility of Adaptive Phenotypes of a Bacterial Metabolic Network","year":2009,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Microbial Metabolic Engineering and Bioproduction","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Kavli Institute for Theoretical Physics, University of California, Santa Barbara; Natural Sciences and Engineering Research Council of Canada; University of California, San Diego; James S. McDonnell Foundation; Advanced Research Projects Agency; Defense Advanced Research Projects Agency; Alfred P. Sloan Foundation","keywords":"Phenotype; Adaptation (eye); Biology; Population; Evolutionary biology; Phenotypic plasticity; Genotype; Adaptive evolution; Flux (metallurgy); Genetics; Computational biology; Ecology; Gene; Neuroscience; 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":[0.001220277,0.0002899568,0.0003470597,0.0008128475,0.0003047472,0.000720043,0.0002913623,0.0004286134,0.0006020717],"category_scores_gemma":[0.01602032,0.0002587691,0.0004967829,0.0003974998,0.00139048,0.001420158,0.0009760993,0.0006752454,0.00006461672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005100836,"about_ca_system_score_gemma":0.000183412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007429771,"about_ca_topic_score_gemma":0.0005421829,"domain_scores_codex":[0.999436,0.000277448,0.0000280932,0.0001069123,0.00009700194,0.0000545055],"domain_scores_gemma":[0.9877408,0.009034865,0.001669278,0.0008911591,0.000345127,0.0003187183],"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":[0.0004038461,0.00006816685,0.0580361,0.0001218593,0.0002123117,0.0004219725,0.0003739377,0.8450075,0.06277192,0.01767802,0.0001262055,0.01477823],"study_design_scores_gemma":[0.00002358044,0.000235778,0.08909398,0.00002485501,0.00007199508,0.0004118489,0.0001094084,0.8664892,0.0141606,0.02896946,0.000334007,0.00007522461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651569,0.0001112064,0.03371558,0.00009144284,0.000002933807,0.000007510919,0.00005311216,0.00007882279,0.0007825225],"genre_scores_gemma":[0.9977449,0.00003850348,0.002117464,0.000006104837,0.000002395376,0.000005241647,0.00003121243,0.000008202564,0.00004604007],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001220277,"threshold_uncertainty_score":0.006453514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01347162564377536,"score_gpt":0.2380069403314466,"score_spread":0.2245353146876712,"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."}}