{"id":"W2615261953","doi":"10.1016/j.neurobiolaging.2017.05.009","title":"NeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases","year":2017,"lang":"en","type":"article","venue":"Neurobiology of Aging","topic":"Neurological diseases and metabolism","field":"Neuroscience","cited_by":158,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"National Institute on Aging; Parkinson's UK; Medical Research Council; Barts Charity; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Bundesministerium für Bildung und Forschung; National Institute for Health and Care Research; National Institute of Environmental Health Sciences; Burroughs Wellcome Fund; EU Joint Programme – Neurodegenerative Disease Research; Huffington Foundation; National Institutes of Health; U.S. Department of Health and Human Services","keywords":"Corticobasal degeneration; Amyotrophic lateral sclerosis; Genotyping; Progressive supranuclear palsy; Frontotemporal dementia; Lewy body; Dementia; Population; Haplotype; Disease; Computational biology; Biology; Genetics; Medicine; Genotype; Pathology; Gene","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003000442,0.001683253,0.001555805,0.003334298,0.0007330121,0.002105018,0.001700306,0.001843235,0.01806513],"category_scores_gemma":[0.008350138,0.001364722,0.001207397,0.002112125,0.0003284505,0.000916184,0.001718665,0.001733971,0.008721706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008031012,"about_ca_system_score_gemma":0.001708155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005519527,"about_ca_topic_score_gemma":0.01930525,"domain_scores_codex":[0.9965604,0.0005865139,0.0003460317,0.0008863345,0.001269887,0.0003507822],"domain_scores_gemma":[0.9958535,0.001713241,0.0005394217,0.0006433249,0.000858962,0.0003915503],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004046432,0.0005113275,0.06176507,0.0007954274,0.001148061,0.001133356,0.0003497114,0.003751548,0.08019272,0.00289704,0.5396942,0.3037151],"study_design_scores_gemma":[0.002144995,0.001097829,0.2205067,0.0004011351,0.00137103,0.006807234,0.000151121,0.0124217,0.1056736,0.00978441,0.6389154,0.0007247662],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.129537,0.005909587,0.1491457,0.006335535,0.005325858,0.001732519,0.6300408,0.0348626,0.03711034],"genre_scores_gemma":[0.1182054,0.003225818,0.2856232,0.01105133,0.003012434,0.006115102,0.4736464,0.006825775,0.09229452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01806513,"threshold_uncertainty_score":0.06043386,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03496606427376271,"score_gpt":0.2760305592598449,"score_spread":0.2410644949860822,"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."}}