{"id":"W4244758980","doi":"10.1554/05-502.1","title":"ASSORTATIVE MATING FOR FITNESS AND THE EVOLUTION OF RECOMBINATION","year":2006,"lang":"en","type":"article","venue":"Evolution","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Assortative mating; Biology; Recombination; Mating; Evolutionary biology; Selection (genetic algorithm); Linkage (software); Genetic Fitness; Mutation; Genetics; Biological evolution; Gene; Machine learning","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":[0.00197705,0.0005789867,0.0008342619,0.0008624081,0.0008174489,0.001727683,0.0007767529,0.001169417,0.003378263],"category_scores_gemma":[0.005456976,0.0003006829,0.0007079935,0.0008121251,0.001192458,0.002454551,0.001055182,0.0009028147,0.0004149663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001313905,"about_ca_system_score_gemma":0.0005070466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006497419,"about_ca_topic_score_gemma":0.0007108756,"domain_scores_codex":[0.999119,0.0003774812,0.00004008757,0.0001636315,0.000156331,0.0001433256],"domain_scores_gemma":[0.9974676,0.001278299,0.0006555347,0.0002750426,0.0001089391,0.0002145154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005575253,0.0001824717,0.1450766,0.0003803769,0.0005500554,0.002728055,0.001214039,0.1397953,0.3145427,0.3431669,0.000909195,0.0508968],"study_design_scores_gemma":[0.00009457106,0.0005904663,0.196813,0.00008935783,0.000306077,0.00567756,0.001025486,0.3545217,0.03758763,0.3922272,0.01077611,0.0002908403],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9638696,0.001887499,0.02662646,0.0009274579,0.00004409752,0.00001658328,0.00005457867,0.00006419615,0.006509473],"genre_scores_gemma":[0.996094,0.0004568841,0.002583221,0.0000819102,0.0000160533,0.00001034287,0.00002955538,0.00001493221,0.0007130598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003378263,"threshold_uncertainty_score":0.01130146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003307408277442299,"score_gpt":0.2274475049656831,"score_spread":0.2241400966882408,"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."}}