{"id":"W2033351747","doi":"10.1534/genetics.106.062406","title":"The Distribution of Beneficial Mutant Effects Under Strong Selection","year":2006,"lang":"en","type":"article","venue":"Genetics","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biology; Selection (genetic algorithm); Fixation (population genetics); Genetics; Neutral mutation; Mutant; Evolutionary biology; Distribution (mathematics); Allele; Population; Natural selection; Mutation; Genetic drift; Genetic variation; Gene; Mathematics; Computer science","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":[0.001437856,0.0002578272,0.000443609,0.0007347752,0.0003128517,0.000772501,0.0006041633,0.0004578223,0.001825369],"category_scores_gemma":[0.005756946,0.0002295967,0.0002188743,0.0003590981,0.001170021,0.001125467,0.000789659,0.0006107605,0.0003151835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004782541,"about_ca_system_score_gemma":0.0002523164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002833717,"about_ca_topic_score_gemma":0.0002809857,"domain_scores_codex":[0.9995279,0.0001177871,0.00001975781,0.0001504768,0.0001206184,0.00006350513],"domain_scores_gemma":[0.9973119,0.001600642,0.0003525319,0.0003194019,0.0002498401,0.0001657562],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0006202692,0.0001501432,0.07173187,0.0004350826,0.0002299148,0.001598693,0.0007579115,0.178815,0.337448,0.3237565,0.0018144,0.08264216],"study_design_scores_gemma":[0.0001140336,0.0004779032,0.1306515,0.00005733003,0.0001526961,0.003090406,0.0003325458,0.4747976,0.05296981,0.3330475,0.004132217,0.0001765403],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8738343,0.000634714,0.1155559,0.0002247993,0.00001523093,0.00002315191,0.0001788868,0.000245805,0.009287294],"genre_scores_gemma":[0.9966086,0.0001545622,0.002513468,0.00004488319,0.0000132443,0.00001330869,0.00006656087,0.00001771583,0.0005677526],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001825369,"threshold_uncertainty_score":0.007604182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00303357075860976,"score_gpt":0.2178527743633168,"score_spread":0.2148192036047071,"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."}}