Using a Spatial Navigation Task to Understand Potential Early Cognitive Changes in Older Adults at Risk for Cognitive Decline
Bibliographic record
Abstract
Current neuropsychological assessments lack the sensitivity to detect early, and subtle declines in cognition. Groups of individuals known to be at increased risk for later cognitive impairment include older adults with subjective cognitive decline (SCD) and older adults with hearing loss (HL). Locomotor spatial navigation tasks may be more sensitive to these declines; therefore, the current study used a locomotor triangle completion task to examine whether older adults with SCD and older adults with HL displayed worse navigational accuracy compared to age-matched controls, particularly under tasks of increased cognitive load (i.e., dual-task “navigating while listening”). While navigational accuracy was worse under tasks of increased cognitive load, no significant group-related differences were observed. Gait speed was slower under tasks of increased cognitive load, particularly when spatial memory recall was required. Consistent with previous literature, the at-risk groups showed significantly slower gait speed than age-matched controls under tasks of increased cognitive load.
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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) | 0.000 | 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".