{"id":"W4404476326","doi":"10.1101/2024.11.16.623954","title":"When sexual selection meets genetic drift: the coevolution of male traits and female preferences in finite populations","year":2024,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Coevolution; Selection (genetic algorithm); Sexual selection; Biology; Evolutionary biology; Antagonistic Coevolution; Sexual conflict; Computer science; Artificial intelligence","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":[0.001068624,0.0001349059,0.0005260116,0.0004485706,0.0003866581,0.001051368,0.0005428345,0.0006195289,0.001431621],"category_scores_gemma":[0.004716292,0.0002363065,0.000338342,0.000325577,0.001110609,0.001117975,0.0008282457,0.0006535938,0.0001398466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006239236,"about_ca_system_score_gemma":0.0002762182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008987272,"about_ca_topic_score_gemma":0.0009166403,"domain_scores_codex":[0.9995375,0.0001782393,0.00002989227,0.0001189432,0.00008539978,0.00005003913],"domain_scores_gemma":[0.9983429,0.0009281142,0.0003578054,0.0001470252,0.00006289447,0.0001614112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006598584,0.0002988263,0.1885216,0.000424542,0.0006090727,0.003132012,0.001709327,0.08188421,0.4736301,0.1681562,0.002373589,0.0786007],"study_design_scores_gemma":[0.0001435651,0.0006442946,0.3037058,0.0001228091,0.00035392,0.003771144,0.001608234,0.3983497,0.03879053,0.2479878,0.004267297,0.0002547597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796947,0.0002920546,0.01753435,0.0003579144,0.00001520181,0.000006020313,0.00004019216,0.0000623349,0.001997253],"genre_scores_gemma":[0.9983644,0.00005455912,0.001324192,0.0000773592,0.00000624897,0.00000656342,0.00001468823,0.000006784914,0.0001450343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001431621,"threshold_uncertainty_score":0.005651474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01646139603869886,"score_gpt":0.2362972297982064,"score_spread":0.2198358337595075,"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."}}