{"id":"W4248951461","doi":"10.1554/0014-3820(2001)055[2126:egcfmo]2.0.co;2","title":"ESTIMATING GENETIC CORRELATIONS FROM MEASUREMENTS OF FIELD-CAUGHT WATERSTRIDERS","year":2001,"lang":"en","type":"article","venue":"Evolution","topic":"Animal Behavior and Reproduction","field":"Agricultural and Biological Sciences","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Heritability; Biology; Genetic similarity; Similarity (geometry); Statistics; Sample size determination; Field (mathematics); Estimation; Genetic correlation; Sample (material); Evolutionary biology; Genetic variation; Genetics; Mathematics; Demography; Genetic diversity; Computer science; Artificial intelligence; Population; Physics","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":[0.00364699,0.0005247346,0.0008018272,0.0009905947,0.0003000568,0.0003275059,0.0007053317,0.0005870132,0.0008058336],"category_scores_gemma":[0.01489151,0.0004795495,0.0002860735,0.0006799514,0.0004892467,0.0005375696,0.000436747,0.0007354603,0.0003305685],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003340495,"about_ca_system_score_gemma":0.0002415343,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002859511,"about_ca_topic_score_gemma":0.006618829,"domain_scores_codex":[0.9976619,0.001138714,0.0001284485,0.0006435252,0.0003766605,0.00005072943],"domain_scores_gemma":[0.9937622,0.004001522,0.0009028494,0.0006408623,0.0006115639,0.00008105669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007234222,0.0002221485,0.4536044,0.0005166911,0.0006979798,0.000599077,0.001251696,0.01433388,0.2120057,0.0024694,0.00357283,0.3100028],"study_design_scores_gemma":[0.000164802,0.001055787,0.8340505,0.00007472259,0.0002780812,0.0009267517,0.0003099491,0.09682852,0.05477317,0.004489716,0.006881188,0.0001668688],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7631844,0.0005762408,0.2335812,0.0001682651,0.0001056832,0.0001846234,0.0006606334,0.0002627741,0.001276062],"genre_scores_gemma":[0.7174478,0.0003612149,0.2787738,0.0001243159,0.0001013077,0.0003554997,0.0008050319,0.00009898681,0.00193192],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00364699,"threshold_uncertainty_score":0.01928735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04505456957511644,"score_gpt":0.2382955632638096,"score_spread":0.1932409936886932,"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."}}