{"id":"W2053450368","doi":"10.1038/ng1751","title":"Distribution of fitness effects among beneficial mutations before selection in experimental populations of bacteria","year":2006,"lang":"en","type":"article","venue":"Nature Genetics","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":275,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University; University of Ottawa","funders":"","keywords":"Biology; Selection (genetic algorithm); Evolutionary biology; Population; Genetics; Genetic Fitness; Mutation; Pseudomonas fluorescens; Experimental evolution; Fitness landscape; Gene; Bacteria; Demography","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":[],"consensus_categories":[],"category_scores_codex":[0.0000550739,0.000105207,0.0001217664,0.000056409,0.00003783041,0.000005024905,0.00007900639,0.0003324632,0.00000504605],"category_scores_gemma":[0.00002878596,0.0001157483,0.00006215137,0.0002037349,0.00007329631,0.000003004093,0.00003273073,0.0001035938,3.171996e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002890615,"about_ca_system_score_gemma":0.00004196735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006464524,"about_ca_topic_score_gemma":0.001264871,"domain_scores_codex":[0.9992682,0.00003721691,0.0002698261,0.0001745899,0.0001205319,0.0001296128],"domain_scores_gemma":[0.9996147,0.000004868798,0.0001248966,0.0001147713,0.000116533,0.00002421479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000382576,0.0002523172,0.3471363,0.00004127725,0.00001320589,3.825357e-7,0.00004466692,0.01937686,0.6318097,0.0007727544,0.0001459723,0.0003683299],"study_design_scores_gemma":[0.0003349618,0.000147657,0.6987914,0.00001052687,0.00001282129,0.000001805256,0.00001940448,0.002445085,0.2978318,0.0002467176,0.00008280381,0.00007496723],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958886,0.0006489822,0.002910683,0.00001064097,0.0001825637,0.0001953618,0.00008562435,0.000005834493,0.0000716955],"genre_scores_gemma":[0.9961623,0.000008938277,0.001703213,0.000007061236,0.0001178476,0.00001195538,0.001925704,0.00001211465,0.00005084414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3516551,"threshold_uncertainty_score":0.472008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003184044395411992,"score_gpt":0.2537207530812448,"score_spread":0.2505367086858328,"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."}}