Classification of <i>GBA1</i> variants in Parkinson’s disease; the <i>GBA1</i> -PD browser
Bibliographic record
Abstract
ABSTRACT Background GBA1 variants are among the most common genetic risk factors for Parkinson’s Disease (PD). GBA1 variants can be classified into three categories based on their role in Gaucher’s Disease (GD) or PD: severe, mild, and risk variant (for PD). Objectives This paper aims to generate and share a comprehensive database for GBA1 variants reported in PD to support future research and clinical trials. Methods We performed a literature search for all GBA1 variants that have been reported in PD. The data has been standardized and complimented with variant classification, Odds Ratio (OR) if available and other data. Results We found 371 GBA1 variants reported in PD: 22 mild, 84 severe, 3 risk variants, and 262 of unknown status. We created a browser, containing up-to-date information on these variants ( https://pdgenetics.shinyapps.io/GBA1Browser/ ). Conclusions The classification and browser presented in this work should inform and support basic, translational, and clinical research on GBA1 -PD.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.017 |
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".