{"id":"W2952321693","doi":"10.1002/evl3.98","title":"Indirect genetic effects clarify how traits can evolve even when fitness does not","year":2019,"lang":"en","type":"article","venue":"Evolution Letters","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Guelph","funders":"","keywords":"Maladaptation; Natural selection; Fitness landscape; Adaptation (eye); Selection (genetic algorithm); Context (archaeology); Social evolution; Inclusive fitness; Adaptability; Genetic Fitness; Variance (accounting); Evolutionary biology; Biology; Computer science; Ecology; Artificial intelligence; Population; Genetics; Economics; Sociology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001560773,0.0002859189,0.0002403949,0.0001072105,0.0001086248,0.00004626827,0.0003099729,0.0004075471,0.00005083774],"category_scores_gemma":[0.00006927215,0.0002562221,0.0001714823,0.000121006,0.0001081687,0.000008766052,0.0001037724,0.0002848409,0.00007852199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001131961,"about_ca_system_score_gemma":0.0001003936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000500909,"about_ca_topic_score_gemma":0.0001923055,"domain_scores_codex":[0.9982419,0.0001745658,0.0002111545,0.0006045401,0.0002936211,0.0004742064],"domain_scores_gemma":[0.9991637,0.00002478421,0.000127846,0.0004596938,0.00007703408,0.0001469454],"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":[0.00007244389,0.00005719198,0.03514273,0.00009816067,0.0001319609,0.000006584783,0.0001704378,0.003804088,0.9340273,0.0001031186,0.02506432,0.001321715],"study_design_scores_gemma":[0.003079959,0.0005061499,0.9034,0.0000821202,0.000123453,0.00005493616,0.0001069746,0.008366843,0.05121765,0.0002751489,0.03148664,0.001300122],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9677829,0.0005522508,0.0235512,0.006388713,0.0008617315,0.0005406176,0.00006058414,0.00005746826,0.0002045505],"genre_scores_gemma":[0.9899095,0.00005152049,0.001802465,0.003927784,0.0003903901,0.00004469419,0.0001604612,0.00004683745,0.003666306],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8828096,"threshold_uncertainty_score":0.999989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003399164697165218,"score_gpt":0.1932198512809079,"score_spread":0.1898206865837427,"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."}}