Repeatability of measurement in determining stature in sitting and standing postures
Bibliographic record
Abstract
The aim of this study was to determine the effect of sitting and standing postures on the repeatability of a stadiometer designed to detect small variations in spinal length. Two groups of ten healthy subjects, with no previous or known history of back problems, participated in this study. One group was measured in the standing posture, while the other group was measured in a sitting posture. All subjects gave informed consent to participate in this study. Subjects had a set of landmarks defining the spinal contour marked on their backs and then stood in the stadiometer for three series of ten measurements to be performed. At the end of each measurement, the subjects were requested to move away from and then be repositioned in the stadiometer. Subjects improved the repeatability across the measurement series. At the end of the second measurement series, all subjects presented mean standard deviations of 0.43 +/- 0.08 mm (range 0.30-0.50 mm) in the standing posture. In the sitting posture, deviations of less than 0.05 mm were obtained only at the end of the third measurement series (0.48 +/- 0.08 mm; range 0.34-0.62 mm), suggesting that this posture required three measurement series before repeatable measurements could be assured rather than two in the standing posture.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".