{"id":"W4298174681","doi":"10.17615/hd56-mp91","title":"Characteristics of magnetic resonance imaging biomarkers in a natural history study of golden retriever muscular dystrophy","year":2020,"lang":"en","type":"article","venue":"UNC Libraries","topic":"Mitochondrial Function and Pathology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"North Carolina Translational and Clinical Sciences Institute, University of North Carolina at Chapel Hill; National Institute of Arthritis and Musculoskeletal and Skin Diseases; National Institute of Neurological Disorders and Stroke; Intellectual and Developmental Disabilities Research Center; U.S. Public Health Service; National Institutes of Health; Muscular Dystrophy Association","keywords":"Muscular dystrophy; Natural history; Labrador Retriever; Magnetic resonance imaging; Medicine; Nuclear magnetic resonance; Pathology; Anatomy; Radiology; Internal medicine; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005720938,0.0001138601,0.000219279,0.0000545926,0.00001349284,0.00000611976,0.0001584426,0.00006770217,0.00007485236],"category_scores_gemma":[0.0002010634,0.0001113454,0.00005542153,0.0001341265,0.0001448598,0.00001046345,0.0001072609,0.00008987851,0.000001751647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001025849,"about_ca_system_score_gemma":0.00008182602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002975989,"about_ca_topic_score_gemma":0.000006856848,"domain_scores_codex":[0.9991041,0.0001033896,0.0003050693,0.0002591253,0.0001054972,0.0001227762],"domain_scores_gemma":[0.9995612,0.00001569349,0.000114989,0.0002182814,0.00004708782,0.00004277359],"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":[0.002012759,0.0002444334,0.1707112,0.0001099459,0.00005155163,0.00006371724,0.002650157,0.000002458981,0.8119953,0.0009337603,0.007891866,0.003332914],"study_design_scores_gemma":[0.009675623,0.005729802,0.5168792,0.0001172749,0.0001651557,0.00002745505,0.003575468,0.0005381568,0.1360699,0.0003929346,0.3257143,0.001114657],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893442,0.009333325,0.0001108083,0.0001407347,0.0004686123,0.000226912,0.00002087719,0.00001013603,0.0003444183],"genre_scores_gemma":[0.9980379,0.00002479266,0.001212634,0.0002927191,0.0001168866,0.000006859209,0.00004456391,0.00001511509,0.0002485023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6759253,"threshold_uncertainty_score":0.4540532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0102997783944553,"score_gpt":0.1970580378878427,"score_spread":0.1867582594933875,"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."}}