Towards Standardizing Nomenclature in Huntington’s Disease Research
Bibliographic record
Abstract
The field of Huntington's disease research covers many different scientific disciplines, from molecular biology all the way through to clinical practice, and as our understanding of the disease has progressed over the decades, a great deal of different terminology has accrued. The field is also renowned for its collaborative spirit and use of standardized reagents, assays, datasets, models, and clinical measures, so the use of standardized terms is especially important. We have set out to determine, through a consensus exercise involving basic and clinical scientists working in the field, the most appropriate language to use across disciplines. Nominally, this article will serve as the style guide for the Journal of Huntington's Disease (JHD), the only journal devoted exclusively to HD, and we lay out the preferred and standardized terminology and nomenclature for use in JHD publications. However, we hope that this article will also serve as a useful resource to the HD research community at large and that these recommended naming conventions will be adopted widely.
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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 | 0.088 | 0.087 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".