{"id":"W2023174816","doi":"10.1371/journal.pone.0122558","title":"A Genetic Predictive Model for Canine Hip Dysplasia: Integration of Genome Wide Association Study (GWAS) and Candidate Gene Approaches","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Veterinary Orthopedics and Neurology","field":"Veterinary","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eusko Jaurlaritza","keywords":"Genome-wide association study; Medicine; Population; Genetic association; Single-nucleotide polymorphism; Dysplasia; Genetic testing; Hip dysplasia; Bioinformatics; Genetics; Internal medicine; Genotype; Biology; Surgery; Gene; Radiography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004040147,0.0009614236,0.0008953162,0.001886714,0.0003741866,0.001299839,0.001422038,0.001072996,0.003413942],"category_scores_gemma":[0.006446807,0.000383249,0.001573959,0.00104993,0.0004805232,0.0005344409,0.0008418522,0.000935053,0.000506597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000448084,"about_ca_system_score_gemma":0.001004839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00536738,"about_ca_topic_score_gemma":0.004138723,"domain_scores_codex":[0.9984453,0.001007579,0.0000570356,0.0002696347,0.0001217136,0.00009864591],"domain_scores_gemma":[0.9976403,0.001714196,0.0002199694,0.0001082747,0.0002015884,0.000115727],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002293355,0.0009500398,0.5511474,0.0004622183,0.005553649,0.004791598,0.0005542812,0.2484058,0.007164766,0.03532066,0.005831355,0.1375249],"study_design_scores_gemma":[0.0001337377,0.0005662715,0.04214121,0.00007992684,0.001775145,0.001271297,0.0001553164,0.9336094,0.0003156089,0.01667971,0.0032172,0.00005533815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5035969,0.004895905,0.4749283,0.008764987,0.0004212083,0.0003915138,0.001472177,0.000741081,0.004787983],"genre_scores_gemma":[0.9441211,0.001562009,0.04932771,0.0005639779,0.000245905,0.0003321655,0.0008033611,0.00005302234,0.002990848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00536738,"threshold_uncertainty_score":0.0213666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1890342047390261,"score_gpt":0.2819959561012794,"score_spread":0.09296175136225335,"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."}}