{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001509413,0.00009739652,0.0002194628,0.00004270312,0.00002366492,0.00000114709,0.0001467083,0.0001551997,0.001121223],"category_scores_gemma":[0.0001759588,0.00006947307,0.00006283896,0.00003474665,0.0002449688,6.701578e-7,0.0001164539,0.00004587954,0.00005897973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005928352,"about_ca_system_score_gemma":0.00001788945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000155877,"about_ca_topic_score_gemma":0.000002793719,"domain_scores_codex":[0.9991538,0.00008504793,0.0003809658,0.0001709301,0.00006612534,0.0001431429],"domain_scores_gemma":[0.9995778,0.00003356289,0.0001138324,0.0002163393,0.00001605633,0.00004238576],"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":[0.0002862128,0.0009090003,0.02668805,0.0001172755,0.00005066641,0.000004258938,0.0001127993,0.0001570625,0.9662703,0.003027697,0.001946096,0.0004305454],"study_design_scores_gemma":[0.01783079,0.004157965,0.2098494,0.0005158789,0.0002567296,0.0004130873,0.000260915,0.004102606,0.4829087,0.03850552,0.2380927,0.00310571],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967981,0.00005986457,0.001634598,0.0001633324,0.00004957214,0.0001275159,0.00004954187,0.000003700807,0.001113782],"genre_scores_gemma":[0.9929857,0.00008582187,0.005812662,0.00004541169,0.00003934624,0.00001144532,0.0002460062,0.000007831255,0.0007658003],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4833616,"threshold_uncertainty_score":0.9997919,"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."}}