Spatial navigation: Cognitive variables involved in route retracing among an elderly population
Bibliographic record
Abstract
Summary The cognitive processes involved in route retracing are not well known. This study aims to highlight them in an elderly population in which contradictory results have been obtained, certain studies showing specific difficulties for route retracing, others not. Thirty‐nine elderly subjects performed a route‐learning task (forward‐backward) in a garden, then completed spatial knowledge tasks and standardised cognitive tests. Results show four factors that were predictive of route retracing performance: route repetition, the pointing task, and two standardised cognitive tests, one assessing spatial working memory, and another global cognitive efficiency. According to these results, route retracing involves route and survey knowledge (i.e., egocentric and allocentric strategy), and the integration of forward‐backward perspectives is underpinned by the spatial working memory. Moreover, the subjects did not make more errors in route retracing than in the route repetition task, suggesting that a real environment could compensate for a failing allocentric strategy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".