Comparison of FAP scores with the use of safety footwear and regular walking shoes
Bibliographic record
Abstract
Gait analysis has been used for the assessment of gait-related disabilities and to provide detailed information. The gait characteristics of a healthy adult population have often been utilised to evaluate and monitor a subject's walk and patterns. This paper summarises a study that aims to compare the Functional Ambulation Performance (FAP) scores in male subjects wearing safety shoes versus regular walking shoes (RWS). Participants walked with RWS along the GAITRite® electronic walkway 30 times in self-selected speed and were analysed by the FAP; the subjects then repeated the same procedure with safety footwear. The data were then gathered in test groups containing 15 measured walks enabling the research team to establish an accurate and average FAP score for each test group. A descriptive statistic for the collected data was performed to determine the gait variables of the FAP score. Walking velocity, step and stride length, step and stride time, and step width among other measures were collected by the GAITRite® system and analysed in this research. Results show a slightly lower FAP score for test subjects walking with safety footwear and the parameters mainly affected were the step length and the stride length.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".