{"id":"W2140213234","doi":"10.1111/jbg.12036","title":"Linear and <scp>P</scp>oisson models for genetic evaluation of tick resistance in cross‐bred <scp>H</scp>ereford x <scp>N</scp>ellore cattle","year":2013,"lang":"en","type":"article","venue":"Journal of Animal Breeding and Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Goodness of fit; Statistics; Generalized linear model; Deviance (statistics); Heritability; Linear model; Mathematics; Poisson distribution; Residual; Biology; Genetic model; Random effects model; Tick; Trait; Genetics; Ecology; Computer science; Gene","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":[0.009737953,0.001267158,0.0009863751,0.002028535,0.0004814643,0.001453864,0.001788046,0.0009610493,0.002757531],"category_scores_gemma":[0.01369087,0.0006164628,0.002326977,0.001141248,0.0007143057,0.0006842766,0.001155922,0.0013627,0.0006274879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001193749,"about_ca_system_score_gemma":0.00130725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01646327,"about_ca_topic_score_gemma":0.01248548,"domain_scores_codex":[0.9959442,0.002810434,0.0001459456,0.0004977863,0.0003445225,0.0002570731],"domain_scores_gemma":[0.9897186,0.008420059,0.0008253606,0.0003737317,0.0005219049,0.0001403138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001115035,0.0006658695,0.1074669,0.000203393,0.001670721,0.0007578004,0.001054431,0.811471,0.003757319,0.009271338,0.001315049,0.06125112],"study_design_scores_gemma":[0.00002991047,0.0001879275,0.01033408,0.00002838336,0.0001156454,0.00007723046,0.0001177806,0.985796,0.0002726377,0.002635573,0.0003773338,0.00002756091],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7563471,0.0007389189,0.2395912,0.0004346528,0.00005709652,0.0001696294,0.0006214848,0.0005224894,0.001517443],"genre_scores_gemma":[0.9677546,0.0003203698,0.02625524,0.00004935114,0.00002953407,0.000276517,0.0009245013,0.00009116737,0.004298701],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01646327,"threshold_uncertainty_score":0.05149984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03383024684655733,"score_gpt":0.2855123475243403,"score_spread":0.251682100677783,"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."}}