{"id":"W2075048236","doi":"10.1007/s11538-008-9294-5","title":"Does Dormancy Increase Fitness of Bacterial Populations in Time-Varying Environments?","year":2008,"lang":"en","type":"article","venue":"Bulletin of Mathematical Biology","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"Mount Allison University","funders":"","keywords":"Dormancy; Population; Computer science; Organism; Biology; Mathematical optimization; Mathematics; Control theory (sociology); Biological system; Artificial intelligence; Demography; Genetics; Control (management)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007330669,0.0002384673,0.0004596302,0.0002190175,0.0002639694,0.0007245554,0.0004514959,0.0007405289,0.00151258],"category_scores_gemma":[0.006528376,0.0001895467,0.0004587095,0.0001756744,0.0007524022,0.001362595,0.0004892391,0.0005471613,0.0001165162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003546263,"about_ca_system_score_gemma":0.0001344126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005346832,"about_ca_topic_score_gemma":0.0006200493,"domain_scores_codex":[0.999858,0.00004606191,0.000006792234,0.00002787869,0.00001164583,0.00004950424],"domain_scores_gemma":[0.9979119,0.001111334,0.0004664781,0.0001840971,0.0001006627,0.0002255728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002238854,0.000489414,0.2715642,0.0009122206,0.0007226938,0.002953999,0.001145747,0.1199895,0.3528991,0.134444,0.003730575,0.1089098],"study_design_scores_gemma":[0.0001516273,0.00125633,0.4895836,0.00007796967,0.0003327733,0.001572328,0.00109632,0.350685,0.01605794,0.1365894,0.002474528,0.0001222143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934999,0.0003360585,0.004058531,0.001047609,0.00005226506,0.000002555091,0.00002981833,0.00001569536,0.0009575945],"genre_scores_gemma":[0.9991872,0.000157355,0.0003319281,0.00005604546,0.00002683014,0.000002491312,0.00001092934,0.000006512082,0.0002208844],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00151258,"threshold_uncertainty_score":0.005060136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01249704152452437,"score_gpt":0.2467181067898747,"score_spread":0.2342210652653503,"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."}}