Dual task performance within a functional virtual environment
Bibliographic record
Abstract
Most daily occupations require the ability to perform two or more activities simultaneously (i.e. dual tasking) while adapting to unexpected changes in the environment. When a person has neurological deficits, this ability is usually impaired. Moreover, recent evidence supports a relationship between executive function deficits and dual task performance. Most of the studies that examine the effect of dual tasking on motor and cognitive aspects simultaneously have not been performed in ecological environments and have not examined the effect of different types of perturbations on performance. The purpose of this paper is to present the feasibility of using advanced technology of virtual reality (VR) to identify the neurophysiological mechanisms that underlie dual task performance within a functional virtual environment in people who have executive function deficits. The participants will be tested for their balance, gait and arm functions as they walk in a virtual supermarket, performing tasks at different levels of complexity which require the use of executive functions. The results will increase our knowledge of human performance during multiple task accomplishment in ecologically valid environments.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".