Use of an Anatomical Scalar to Control for Sex-Based Size Differences in Measures of Hyoid Excursion During Swallowing
Bibliographic record
Abstract
PURPOSE: Traditional methods for measuring hyoid excursion from dynamic videofluoroscopy recordings involve calculating changes in position in absolute units (mm). This method shows a high degree of variability across studies but agreement that greater hyoid excursion occurs in men than in women. Given that men are typically taller than women, the authors hypothesized that controlling for participant size might neutralize apparent sex-based differences in hyoid excursion. METHOD: Hyoid excursion in 20 young (<45) healthy volunteers (10 male), stratified by height, was measured in a tightly controlled videofluoroscopic protocol. RESULTS: The study identified an anatomical scalar (C2-C4 length), visible on the videofluoroscopic image, correlated with participant height. This scalar differed significantly between men and women. By incorporating the anatomical scalar as a continuous covariate in repeated measures mixed-model analyses of variance of hyoid excursion, apparent sex-based differences were neutralized. Transforming measures of hyoid excursion into anatomically scaled units achieved the same result, reducing variation attributable to sex-based differences in participant size. CONCLUSIONS: Hyoid excursion during swallowing is dependent on a person's size. If measurements do not control for this source of variation, apparent sex differences in hyoid excursion are seen.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".