{"id":"W1923754397","doi":"10.1046/j.1420-9101.2001.00276.x","title":"Predicting the evolution of sexual size dimorphism","year":2001,"lang":"en","type":"article","venue":"Journal of Evolutionary Biology","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":156,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sexual dimorphism; Biology; Selection (genetic algorithm); Sexual selection; Evolutionary biology; Natural selection; Term (time); Statistics; Zoology; Mathematics; Physics; Computer science; Machine learning","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001501175,0.0002609937,0.0003634763,0.0004999295,0.0002191991,0.0005332108,0.0004323392,0.0005457985,0.000873604],"category_scores_gemma":[0.008335235,0.0003108842,0.0003717786,0.0003479107,0.0004852384,0.0007023441,0.0003494871,0.0004485028,0.0002274971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009802431,"about_ca_system_score_gemma":0.0004213943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004270738,"about_ca_topic_score_gemma":0.00237078,"domain_scores_codex":[0.9997273,0.0001309405,0.00001071583,0.00006687277,0.00004305678,0.00002108277],"domain_scores_gemma":[0.9970362,0.002341726,0.0002069095,0.0001402533,0.0001697805,0.0001051861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001126775,0.00004511462,0.1065451,0.00003521017,0.00007495545,0.0001305956,0.00008832281,0.863827,0.003903077,0.007664305,0.0004373401,0.01713625],"study_design_scores_gemma":[0.000009066019,0.00001831222,0.009245663,0.000002896331,0.000006375402,0.00004300191,0.000007790557,0.984624,0.0008533416,0.00504779,0.0001333409,0.000008356757],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9415113,0.0001373536,0.05648587,0.0002886378,0.00001180482,0.00001066141,0.0001219221,0.00009741635,0.001335114],"genre_scores_gemma":[0.9934656,0.00003802737,0.006097725,0.00002148495,0.000004895542,0.000009346973,0.0000744507,0.00001341945,0.0002749675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004270738,"threshold_uncertainty_score":0.008491755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081905562935635,"score_gpt":0.240574231669136,"score_spread":0.2197551760397796,"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."}}