Executive deficits detected in mild Alzheimer's disease using the antisaccade task
Bibliographic record
Abstract
The antisaccade task, a hands- and language-free metric, may provide a functional index of the dorsolateral prefrontal cortex (DLPFC), a region damaged in the later stages of Alzheimer's disease (AD). Our objective was to determine if patients with mild AD made more errors relative to age-matched controls. Thirty patients with mild AD (Mini Mental Status Exam [MMSE] ≥ 17) and 31 age-matched controls completed a laptop version of the prosaccades and antisaccades tasks. Patients with AD made more antisaccade errors, and corrected fewer errors, than age-matched controls. Error rates, corrected or uncorrected, were not correlated with AD MMSE or Dementia Rating Scale scores. Our findings indicate that antisaccade impairments exist in mild AD, suggesting clinically detectable DLPFC pathology may be present earlier than suggested by previous studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".