Investigating the relationship between veering in gait and proprioceptive feedback in L-PD and R-PD
Bibliographic record
Abstract
Spatial navigation requires integration of sensory signals generated during movement such as vision, proprioception and vestibular information. Individuals with Parkinson's disease (PD) are known to veer and this may be due proprioceptive or visuospatial deficits, yet the link between these deficits and veering has yet to be studied. Given that PD is generally a unilateral disorder, the main objective of this study was to evaluate whether the side affected (LPD or RPD) influenced the direction and magnitude of off-path veering. Thirteen individuals with PD (7 LPD, 6 RPD) completed this study. The participants were examined on three walking conditions in complete darkness: 1) toward a target 2) into open space 3) into open space but limbs illuminated with glow in the dark tape. Both groups deviated to the left side of the path. The magnitude of veering towards the left side was significantly greater in LPD (F(1,11)=6.48, p
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".