{"id":"W3158267591","doi":"10.1002/vetr.481","title":"DNA profiling for juvenile kidney disease in boxers","year":2021,"lang":"en","type":"article","venue":"Veterinary Record","topic":"Renal and related cancers","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Merck Canada Inc. (Canada)","funders":"","keywords":"Citation; Profiling (computer programming); Juvenile; Miller; Computer science; Library science; Genetics; Biology; Ecology; Programming language","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":[0.00004870781,0.0000884475,0.00009252338,0.00002187208,0.00003474004,0.00001083304,0.00007162927,0.00007660761,0.0000226522],"category_scores_gemma":[0.00005885966,0.00008435675,0.00009096684,0.00006962451,0.0000219238,0.000002793305,0.00005419823,0.00005391918,0.00000497482],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001699555,"about_ca_system_score_gemma":0.0001908664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006245744,"about_ca_topic_score_gemma":0.000003192658,"domain_scores_codex":[0.9993552,0.00002675277,0.0001318123,0.0002661211,0.00004143345,0.0001787062],"domain_scores_gemma":[0.9996378,0.000005243129,0.00003010922,0.0001669102,0.00002973536,0.0001301564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008631631,0.00007089417,0.004924237,0.0001548039,0.00003891011,0.0001665915,0.00001772977,0.00007415071,0.9780788,0.00002064983,0.005721,0.009869024],"study_design_scores_gemma":[0.001307008,0.0008651866,0.0008358718,0.0001217255,0.00002281027,0.00004310052,0.00005049886,0.0003529071,0.2262656,0.0002287127,0.7695751,0.0003314932],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971592,0.0007247066,0.0001794226,0.0003583086,0.000486833,0.0001493838,0.00004880972,0.000009023775,0.0008843484],"genre_scores_gemma":[0.9933586,0.0005159911,0.001647096,0.0005560827,0.0002238151,0.0001093837,0.0004180664,0.00002272568,0.003148248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7638541,"threshold_uncertainty_score":0.3439969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01754649956499371,"score_gpt":0.2698248126081474,"score_spread":0.2522783130431537,"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."}}