Visually navigating a virtual world with real-world impairments: A study of visually and spatially guided performance in individuals with mild cognitive impairments
Bibliographic record
Abstract
In recent years, computer technology has evolved such that highly realistic virtual environments (VEs) can be used within a lab setting. Such VEs provide controlled ability to examine behavioral performance across different populations. The primary goal of this investigation was to examine the ability of mild cognitive impaired (MCI) participants to navigate effectively through a realistic, fictional virtual city. A total of 26 healthy control participants (age: 69 +/- 7.7 years; Mini-Mental State Examination, MMSE >or= 29) and 8 MCI patients (age: 72 +/- 7 years, MMSE >or= 26) were recruited. Both groups exhibited similar spatial-navigation ability. However, the MCI groups' ability to use effective visually guided navigation to traverse the VE was significantly compromised compared to healthy controls; a similar performance reduction was also observed when selecting appropriate paths. Though initially groups appear practically indistinguishable in regard to spatially navigating their way through the VE, these data indicate that careful evaluations of behavior in VEs may provide novel ways to differentiate between populations that have historically displayed relatively subtle differences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".