Evaluating the Contributions of Dynamic Flow to Freezing of Gait in Parkinson's Disease
Bibliographic record
Abstract
Although visual cues can improve gait in Parkinson's disease (PD), their underlying mechanism is poorly understood. Previous research suggests that cues contribute optical flow that is essential to elicit gait improvement. The present study manipulated how optic flow was provided, and how this might influence freezing of gait (FOG) in PD. Therefore, three groups; 15 PD FOG, 16 PD non-FOG, and 16 healthy controls were tested in 3 narrow doorway conditions; baseline (Narrow), ground lines (Ground), and laser (Laser). Step length indicated that the PD FOG group was only able to improve with ground lines, while the laser increased gait variability and double support time. These results suggest that optic flow in itself is not enough to elicit gait improvement in PD. When PD patients use visual cues, gait becomes less automatically controlled and hence preplanned conscious control may be an important factor contributing to gait improvement.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".