Vertical Heterophoria and Susceptibility to Visually Induced Motion Sickness
Bibliographic record
Abstract
Motion sickness is reported to be a common symptom in patients with vertical heterophoria. The goal of this study was to assess the relationship between vertical phoria and susceptibility to motion sickness in a nonclinical sample of 43 subjects. Vertical phoria was measured with a Maddox rod after 30 s of occlusion. To evaluate susceptibility to motion sickness, subjects read text while sitting inside a rotating optokinetic drum for 10 min. Subjects rated their level of motion sickness at 1 min intervals during drum rotation and the magnitude of 13 motion sickness symptoms after drum rotation ended. The magnitude of vertical phoria ranged from 0 to 2.13 prism diopters (pd) with a mean of 0.46 pd and correlated significantly with both the maximum rating of motion sickness during drum rotation and the summed symptom score following rotation. A vertical phoria of 0.75 pd discriminated best between subjects with low vs high summed motion sickness symptom scores (p < 0.0001). Introducing a prism to artificially increase the phoria of 12 subjects with vertical phorias <0.75 pd increased motion sickness symptoms in only 1 subject. Prisms that reduced the phoria of subjects with vertical phorias > 0.75 pd reduced motion sickness symptoms in 2 of the 4 subjects tested. The results confirm an association between vertical phoria and motion sickness, but suggest the relationship may not be causal.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".