Dual task prioritization during overground and treadmill walking
Bibliographic record
Abstract
AbstractBackgroundThe dual-task effect on walking performance is different during treadmill and overground walking, though the cause of this difference is unknown. This study examined the effects of task prioritization on overground and treadmill dual-task walking. MethodTwenty-two adults walked overground and on a treadmill under three dual-task conditions: prioritization of walking performance, prioritization of cognitive performance, or no prioritization. ResultsCompared to single-task walking, stride velocity was reduced and stride time variability was increased during dual-task overground walking. During treadmill walking, there was no dual-task effect on walking performance, but cognitive task performance was improved. Prioritization of the cognitive task reduced the dual-task effect on stride velocity during overground walking only, whilst prioritization of the walking task reduced cognitive task performance in both walking modalities. SignificanceThese results corroborate recent findings that the dual-task effects on treadmill walking are not equivalent to those on overground walking. Healthy adults appear to prioritize cognitive task performance during dual-task walking. However, the effects of this prioritization on dual-task performance depend on the walking modality.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".