Antisaccades: A Probe Into The Dorsolateral Prefrontal Cortex in Alzheimer's Disease
Bibliographic record
Abstract
The number of people living with Alzheimer’s Disease (AD) is projected to \nincrease dramatically over the next few decades, making the search for treatments and \ntools to measure the progression of AD increasingly urgent. The antisaccade task, a \nhands- and language-free metric, may provide a functional index of the Dorsolateral \nPrefrontal Cortex (DLPFC), which is damaged in the later stages of AD. Patients with \nAD make significantly more antisaccade errors than controls, however, performance in \nmild AD has remained unexplored. We hypothesized that mild patients will make more \nerrors than controls. Thirty AD patients and 31 age-match controls completed both \nlaptop-based and clinical versions of the antisaccade task. Two thirds of patients with AD \nmade significantly more errors and corrected less of their errors than age-matched \ncontrols. Our findings indicate that antisaccade impairments exist in mild AD, suggesting \nDLPFC 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".