{"id":"W4398176660","doi":"10.1101/2024.05.17.594196","title":"Indirect genetic effects increase the heritable variation available to selection and are largest for behaviours: a meta-analysis","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Variation (astronomy); Meta-analysis; Selection (genetic algorithm); Genetic variation; Evolutionary biology; Biology; Psychology; Genetics; Statistics; Computer science; Mathematics; Medicine; Artificial intelligence; Internal medicine; 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":[0.01276801,0.002424851,0.006711313,0.006260067,0.0007981635,0.003612085,0.002132923,0.002035203,0.00535802],"category_scores_gemma":[0.03267415,0.001098016,0.036093,0.007203708,0.001071535,0.001814685,0.001794919,0.002093803,0.0005426311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001004949,"about_ca_system_score_gemma":0.001372462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006832226,"about_ca_topic_score_gemma":0.01006549,"domain_scores_codex":[0.9886243,0.005401608,0.002115224,0.002608065,0.0008361316,0.0004146012],"domain_scores_gemma":[0.9596897,0.03237241,0.003445222,0.002561112,0.001450157,0.0004814027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"meta_analysis","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.0009875022,0.00003016941,0.09699061,0.05572028,0.827126,0.0004756912,0.0001983352,0.001217715,0.0009566434,0.0005766716,0.00149016,0.01423033],"study_design_scores_gemma":[0.000181325,0.0001316991,0.0582808,0.007517944,0.9279842,0.0003194396,0.0001615933,0.0008371409,0.0003479524,0.001328495,0.002858667,0.00005078884],"study_design_candidate":"meta_analysis","study_design_consensus":"meta_analysis","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.06876779,0.9126644,0.008310783,0.001759774,0.0004925425,0.0001551835,0.006077087,0.0002522551,0.001520243],"genre_scores_gemma":[0.8807048,0.1083644,0.004991326,0.00153825,0.0003096965,0.0003457947,0.002954972,0.00023475,0.0005560642],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01276801,"threshold_uncertainty_score":0.06752455,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686087330483187,"score_gpt":0.2286879469409106,"score_spread":0.2118270736360787,"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."}}