Accuracy of clinical diagnostic criteria for Friedreich's ataxia
Bibliographic record
Abstract
The accuracy of the diagnostic criteria for Friedreich's ataxia proposed by Harding and by the Quebec Cooperative Study on Friedreich's Ataxia was studied in 142 patients with progressive unremitting ataxia of autosomal recessive inheritance or sporadic occurrence. Eighty-eight patients received the molecular diagnosis of Friedreich's ataxia. Traditional diagnostic criteria are characterized by high specificity, but they yield a high number of false-negative diagnoses. We suggest three levels of diagnostic certainty: (1) possible Friedreich's ataxia, defined as sporadic or recessive progressive ataxia with (a) lower limb areflexia and dysarthria, Babinski sign, or electrocardiographic repolarization abnormalities, or (b) with lower limb retained reflexes and electrocardiographic repolarization abnormalities (95% sensitivity and 88% positive predictive value); (2) probable Friedreich's ataxia as defined by Harding's criteria (63% sensitivity and 96% positive predictive value) or by Quebec Cooperative Study on Friedreich's Ataxia criteria (63% sensitivity and 98% positive predictive value); (3) definite diagnosis, molecularly confirmed.
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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 | 0.005 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".