{"id":"W2078510622","doi":"10.1016/j.tree.2010.10.008","title":"Pleiotropy, apparent stabilizing selection and uncovering fitness optima","year":2010,"lang":"en","type":"article","venue":"Trends in Ecology & Evolution","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pleiotropy; Trait; Selection (genetic algorithm); Fitness landscape; Biology; Evolutionary biology; Metric (unit); Genetics; Phenotype; Computer science; Artificial intelligence; Population; Gene","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":[0.0009750921,0.0003756839,0.0005220367,0.0006953136,0.0003372142,0.0007000039,0.0003400636,0.0005526619,0.001159253],"category_scores_gemma":[0.001138543,0.000286351,0.0003051935,0.0005874436,0.0006637796,0.000604268,0.0004076879,0.0007911665,0.0001231905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001490428,"about_ca_system_score_gemma":0.0001359762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001322249,"about_ca_topic_score_gemma":0.0005125409,"domain_scores_codex":[0.9998341,0.00004121468,0.00001032493,0.00006052126,0.00003252505,0.000021217],"domain_scores_gemma":[0.999281,0.000365305,0.0001632322,0.0001136289,0.0000260579,0.00005085553],"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":[0.001201123,0.0001617652,0.1206793,0.0004071694,0.0004208087,0.0007994818,0.0008444796,0.008825084,0.7540754,0.01250912,0.0004739207,0.09960227],"study_design_scores_gemma":[0.0002158384,0.0005875563,0.8438865,0.00007075258,0.0005381518,0.003003508,0.0008077644,0.02788245,0.0464852,0.07309065,0.00327868,0.0001528691],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9945314,0.0007212479,0.00375281,0.0001214293,0.000009598884,0.000002722354,0.0000644195,0.00004480079,0.0007515521],"genre_scores_gemma":[0.9962724,0.0004495753,0.002894189,0.00005052084,0.00001525573,0.000005260698,0.00007280449,0.000016413,0.0002236509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001159253,"threshold_uncertainty_score":0.005156815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01551329944075602,"score_gpt":0.2475357515218352,"score_spread":0.2320224520810792,"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."}}