{"id":"W4250058296","doi":"10.1554/0014-3820(2003)057[1107:tcotgm]2.0.co;2","title":"THE CONSTANCY OF THE G MATRIX THROUGH SPECIES DIVERGENCE AND THE EFFECTS OF QUANTITATIVE GENETIC CONSTRAINTS ON PHENOTYPIC EVOLUTION: A CASE STUDY IN CRICKETS","year":2003,"lang":"en","type":"article","venue":"Evolution","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Science Council; University of British Columbia; McGill University","keywords":"Biology; Evolutionary biology; Divergence (linguistics); Quantitative genetics; Principal component analysis; Selection (genetic algorithm); Matrix (chemical analysis); Zoology; Genetic divergence; Genetic variation; Genetics; Statistics; Genetic diversity; Mathematics","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":[0.001186353,0.0005157657,0.000667016,0.00116934,0.0007059571,0.0007099481,0.0005960316,0.0005386262,0.0005366479],"category_scores_gemma":[0.004000702,0.0002146844,0.0006976773,0.001397034,0.001218954,0.0005095745,0.0005518218,0.0005023281,0.00004616379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009080678,"about_ca_system_score_gemma":0.0002916786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01719004,"about_ca_topic_score_gemma":0.01299491,"domain_scores_codex":[0.9996045,0.0001587645,0.00002864144,0.000129592,0.00003668652,0.00004179683],"domain_scores_gemma":[0.9969657,0.002304415,0.0003304449,0.0001614655,0.00009447788,0.0001435061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001082703,0.0002125627,0.6949257,0.0004418099,0.0008091425,0.007745383,0.001610115,0.1434183,0.1035664,0.006995223,0.0001879089,0.03900494],"study_design_scores_gemma":[0.00004303746,0.0005931158,0.7751999,0.00003321702,0.0002344753,0.002672884,0.001050878,0.2073054,0.008005632,0.004041921,0.0006854159,0.0001339946],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983345,0.0001517074,0.001274717,0.0000118924,4.705361e-7,0.000004024461,0.00004019607,0.000005460733,0.0001770484],"genre_scores_gemma":[0.9980686,0.00007780878,0.00174553,0.000004606241,9.406767e-7,0.000003785198,0.00003268394,0.000005556759,0.00006040385],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01719004,"threshold_uncertainty_score":0.03417999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02163367237239127,"score_gpt":0.2609129196501661,"score_spread":0.2392792472777748,"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."}}