{"id":"W3199723692","doi":"10.3390/genes12091432","title":"Prediction of Genetic Resistance for Scrapie in Ungenotyped Sheep Using a Linear Animal Model","year":2021,"lang":"en","type":"article","venue":"Genes","topic":"Prion Diseases and Protein Misfolding","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Agriculture, Food and Rural Affairs; University of Guelph","funders":"","keywords":"Scrapie; Genotyping; Genotype; Haplotype; Biology; Allele; Selection (genetic algorithm); Veterinary medicine; Genetics; Gene; Medicine; Machine learning; Prion protein","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":[0.0000652417,0.00006769205,0.00008835747,0.00002316253,0.00003265213,0.00000552487,0.00006111678,0.00007281831,0.000006001118],"category_scores_gemma":[0.000042519,0.0000754637,0.00006283601,0.00007013688,0.00001826408,0.000002149153,0.0000432087,0.00001987005,2.233365e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008907888,"about_ca_system_score_gemma":0.0001361236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005067261,"about_ca_topic_score_gemma":0.00004523763,"domain_scores_codex":[0.9994314,0.00002064346,0.0001616437,0.0002043845,0.00005817674,0.000123701],"domain_scores_gemma":[0.9996614,0.000004195163,0.00004675839,0.0001663327,0.00009035209,0.00003091067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001783115,0.00002794862,0.00286808,0.00007233902,0.00001885964,0.000001607285,0.0000167677,0.01134288,0.9831039,0.00002411869,0.00004484113,0.002300292],"study_design_scores_gemma":[0.0007960622,0.00009615836,0.005114344,0.00005115706,0.00004167696,0.000003161479,0.00003189685,0.102949,0.8869361,0.000423183,0.003411744,0.0001455652],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9336501,0.0375381,0.02847858,0.00003433014,0.00003686323,0.0001374688,0.00009797759,0.000003911009,0.00002267574],"genre_scores_gemma":[0.953538,0.001322397,0.04479128,0.00005041368,0.0001212558,0.00001929334,0.00005623675,0.00001394129,0.00008717164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09616787,"threshold_uncertainty_score":0.307732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03562536838377351,"score_gpt":0.2754934596185871,"score_spread":0.2398680912348136,"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."}}