{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000568112,0.000045735,0.00005446338,0.000006182496,0.0001033084,0.000006606913,0.00004817062,0.00004485281,0.0002765116],"category_scores_gemma":[0.00003758572,0.00001902651,0.00003522776,0.000118355,0.00001601513,0.00006860721,0.00001168267,0.00003991351,0.00002398171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002541785,"about_ca_system_score_gemma":0.000002771659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001357526,"about_ca_topic_score_gemma":0.000179262,"domain_scores_codex":[0.9995315,0.00002325785,0.000125637,0.0001324809,0.0001041484,0.00008294791],"domain_scores_gemma":[0.9998232,0.00002194224,0.00005570119,0.00003187771,0.00004499002,0.00002232184],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001549114,0.00003630391,0.4317454,7.959171e-7,0.000004419569,3.15073e-7,0.00004135108,0.0002880681,0.5460443,0.000005790331,0.0003072197,0.02151053],"study_design_scores_gemma":[0.00005722333,0.00006985224,0.9921461,0.00001225289,0.00001840818,0.000002729892,0.00007927221,0.0008186954,0.0062013,0.0003377672,0.0001991594,0.00005729187],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974985,0.00009065249,0.001374961,0.0004016904,0.00027653,0.00007212131,0.000003607223,0.00002709184,0.0002548622],"genre_scores_gemma":[0.9984144,0.000002803773,0.001169995,0.000009457953,0.0002265087,0.000002981212,0.000028109,3.29133e-7,0.000145407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5604006,"threshold_uncertainty_score":0.3027608,"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."}}