{"id":"W2081840097","doi":"10.1172/jci69411","title":"Metabolic network as a progression biomarker of premanifest Huntington’s disease","year":2013,"lang":"en","type":"article","venue":"Journal of Clinical Investigation","topic":"Genetic Neurodegenerative Diseases","field":"Neuroscience","cited_by":122,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Institute of Neurological Disorders and Stroke; University of California, San Diego; University of Toronto; CHDI Foundation; National Institutes of Health; Pfizer","keywords":"Medicine; Huntington's disease; Putamen; Biomarker; Metabolic network; Cohort; Disease; Internal medicine; Neuroimaging; Imaging biomarker; Oncology; Pathology; Bioinformatics; Magnetic resonance imaging; Biology; Radiology; Psychiatry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005876931,0.0003069209,0.0002201317,0.000858676,0.0001507736,0.0004050993,0.000165875,0.0003003966,0.0006888289],"category_scores_gemma":[0.001774325,0.0001053761,0.000182625,0.0003377528,0.0001729168,0.0003004184,0.0002789659,0.0002969647,0.00007988938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003394963,"about_ca_system_score_gemma":0.0002057495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002307879,"about_ca_topic_score_gemma":0.00370814,"domain_scores_codex":[0.9999068,0.00002995074,0.000007041729,0.00002878707,0.00001742695,0.00001003041],"domain_scores_gemma":[0.9992707,0.0002434865,0.0003052209,0.00004632049,0.00006958982,0.00006475297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007900127,0.0001079498,0.9639349,0.00003750157,0.0001614669,0.0001466142,0.000119809,0.005814992,0.01087455,0.0002633443,0.0001693784,0.0175794],"study_design_scores_gemma":[0.00001357056,0.0002912212,0.9719747,0.00000833994,0.00006237847,0.0003305789,0.00005695902,0.02449177,0.001939249,0.000574054,0.0002482211,0.000009027193],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977213,0.0001420768,0.001528961,0.00003523759,0.000001909897,0.0000141424,0.0002326734,0.00001463582,0.0003091104],"genre_scores_gemma":[0.9983343,0.00007496992,0.001182266,0.000005907428,0.00000294435,0.000009888316,0.0003137172,0.000001910021,0.00007402706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002307879,"threshold_uncertainty_score":0.004588902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09943676473839468,"score_gpt":0.3908154313540809,"score_spread":0.2913786666156862,"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."}}