Identification of common variants influencing risk of the tauopathy progressive supranuclear palsy
Bibliographic record
Abstract
CurePSP Foundation, the Peebler PSP Research Foundation, and National Institutes on Health (NIH) grants R37 AG 11762, R01 PAS-03-092, P50 NS72187, P01 AG17216 [National Institute on Aging(NIA)/NIH], MH057881 and MH077930 [National Institute of Mental Health (NIMH)]. Work was also supported in part by the NIA Intramural Research Program, the German National Genome Research Network (01GS08136-4) and the Deutsche Forschungsgemeinschaft (HO 2402/6-1), Prinses Beatrix Fonds (JCvS, 01–0128), the Reta Lila Weston Trust and the UK Medical Research Council (RdS: G0501560). The Newcastle Brain Tissue Resource provided tissue and is funded in part by a grant from the UK Medical Research Council (G0400074), by the Newcastle NIHR Biomedical Research Centre in Ageing and Age Related Diseases to the Newcastle upon Tyne Hospitals NHS Foundation Trust, and by a grant from the Alzheimer’s Society and Alzheimer’s Research Trust as part of the Brains for \nDementia Resarch Project. We acknowledge the contribution of many tissue samples from the Harvard Brain Tissue Resource Center. We also acknowledge the 'Human Genetic Bank of Patients affected by Parkinson Disease and parkinsonism' (http://www.parkinson.it/dnabank.html) of the Telethon Genetic Biobank Network, supported by TELETHON Italy (project n. GTB07001) and by Fondazione Grigioni per il Morbo di Parkinson. The University of Toronto sample collection was supported by grants from Wellcome Trust, Howard Hughes Medical Institute, and the Canadian Institute of Health Research. Brain-Net-Germany is supported by BMBF (01GI0505). RdS, AJL and JAH are funded by the Reta Lila Weston Trust and the PSP (Europe) Association. RdS is funded by the UK Medical Research Council (Grant G0501560) and Cure PSP+. ZKW is partially supported by the NIH/NINDS 1RC2NS070276, NS057567, P50NS072187, Mayo Clinic Florida (MCF)Research Committee CR programs (MCF #90052030 and MCF #90052030), and the gift from Carl Edward Bolch, Jr., and Susan Bass Bolch (MCF #90052031/PAU #90052). The Mayo Clinic College of Medicine would like to acknowledge Matt Baker, Richard Crook, Mariely DeJesus-Hernandez and Nicola Rutherford for their preparation of samples. PP was supported by a grant from the Government of Navarra ("Ayudas para la Realización de Proyectos de Investigación" 2006–2007) and acknowledges the "Iberian Atypical Parkinsonism Study Group Researchers", i.e. Maria A. Pastor, Maria R. Luquin, Mario Riverol, Jose A. Obeso and Maria C Rodriguez-Oroz (Department of Neurology, Clínica Universitaria de Navarra, University of Navarra, Pamplona, Spain), Marta Blazquez (Neurology Department, Hospital Universitario Central de Asturias, Oviedo, Spain), Adolfo Lopez de Munain, Begoña Indakoetxea, Javier Olaskoaga, Javier Ruiz, José Félix Martí Massó (Servicio de Neurología, Hospital Donostia, San Sebastián, Spain), Victoria Alvarez (Genetics Department, Hospital Universitario Central de Asturias, Oviedo, Spain), Teresa Tuñon (Banco de Tejidos Neurologicos, CIBERNED, Hospital de Navarra, Navarra, Spain), Fermin Moreno (Servicio de Neurología, Hospital Ntra. Sra. de la Antigua, Zumarraga, Gipuzkoa, Spain), Ainhoa Alzualde (Neurogenétics Department, Hospital Donostia, San Sebastián, Spain).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".