Bibliographic record
Abstract
The inherited ataxias are disorders that cause progressive imbalance as a result of pathology in the cerebellum and its various connecting pathways. Autosomal recessive ataxias include Friedreich ataxia, ataxia with isolated vitamin E deficiency, ataxia-telangiectasia, and autosomal recessive ataxia of Charlevoix-Saguenay, among others. A discussion of autosomal dominant ataxias covers spinocerebellar ataxias (SCA) types 1 through 14, dentatorubral pallidoluysian atrophy (DRPLA), and episodic ataxia (EA) syndromes. Clinical features, laboratory studies, differential diagnosis, and management of inherited ataxias are discussed. Tables describe both autosomal recessive ataxias and autosomal dominant ataxias (with known gene loci), childhood– or young adult–onset ataxias with ill-defined genetic abnormalities, phenotypic features that may indicate a specific genotype in the common autosomal dominant ataxias, and normal and expanded ranges of various repetitive nucleotide sequences in inherited ataxias. Figures include a diagrammatic representation of the type of repeat expansions associated with ataxias, aggregates of ataxin 3, a schematic of some of the proposed pathogenic mechanisms in the polyglutamine ataxias, and dystonia in a patient with SCA3. A sidebar offers selected Internet resources for information on ataxias. This chapter contains 64 references.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.047 | 0.022 |
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".