The Influence of Lateral Constraints on Walking: Effects of Walking Speed and Biological Sex
Bibliographic record
Abstract
This study examined the influence of lateral constraints and sex on walking in different settings. Thirty-eight adults (17 males: 25 [3] y, 21 females: 24 [4] y) walked overground for 20 m in open (no constraints), open pathway (defined by lines on the floor), and hallway (pathway defined by walls) settings at 3 speeds (slow, preferred, and fast). Inertial sensors recorded kinematics (Xsens Awinda, Movella) to calculate stride velocity, stride length (SL), cadence, and double support phase percentage. Stride velocity, SL, and cadence were also normalized to account for body size. Linear mixed models were used for statistical analysis (α = .05). No setting or setting by speed effects were found. Males had greater SL compared with females at preferred and fast speeds. Males had greater normalized SL compared with females at fast speeds. Females had greater cadence compared with males across conditions. Males had greater double support phase percentage compared with females at slow speeds. Wider hallways may allow for walking assessments generalizable to open settings. Considering sex differences in cadence at any speed, SL at preferred and fast speeds, normalized SL at fast speeds, and double support phase percentage at slow speeds may be valuable for interpreting walking assessments.
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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 | 0.005 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".