Estudio de la calidad de la medida de cargas ejercidas sobre bastones canadienses instrumentados
Bibliographic record
Abstract
Introduction: nowadays, we have not found any weight measurement system adapted to Canadian crutches, which could feasibly be used in daily clinical practice to recognize and correct the force applied on these canes by patients with assisted mobility. Objective: to understand the measurement quality of weight exerted with Canadian crutches that we have implemented as the first step in validating a system. We developed this system to measure such weights and enter them in a computerized database of measurement. Materials and method. Design: Experimental study of measurements and of consistency. Variables: applied mass, measurements made by the crutches and errors in the measurements. Equipment: nine calibrated weights from 5 to 45 kg. Confidence interval 95 %. Results: the analysis of reliability through the intra-class correlation coefficient and through the Cronbach alpha, as well as the correlation between real and observed variables, using the Spearman and Pearson´s coefficient 1 (p 0.05. The average error of measurements was 0.1097, adjusting the variable error to the normal distribution (p > 0.05 in the Shapiro-Wilk test). Discussion: the error, which is considered random, is 110 g, indicating very low levels of the same nature, which range from 62 to 167 g. Therefore, we accept that there isn’t a difference in between the real and observed measurements with the right and left cane. Conclusions: the Canadian crutches that we have introduced have become a reliable and valid tool for measuring weights applied by calibrated weights. The use of one cane or another is irrelevant, considering there are no significant differences in their measurements.
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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 | 0.006 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".