Measurement of oscillopsia induced by vestibular Coriolis stimulation
Bibliographic record
Abstract
We demonstrate a new method for measuring the time constant of head-movement-contingent oscillopsia (HMCO) produced by vestibular Coriolis stimulation. Subjects briskly rotated their heads around pitch or roll axes whilst seated on a platform rotating at constant velocity. This induced a cross-coupled vestibular Coriolis illusion. Simultaneous with the head movement, a visual display consisting of either a moving field of white dots on a black background or superimposed on a subject-stationary horizon, or a complete virtual room with conventional furnishings appeared. The scene's motion was driven by a simplified computer model of the Coriolis illusion. Subjects either nulled (if visual motion was against the illusory body rotation) or matched (if motion was in the same direction as the illusory motion) the sensation with the exponentially slowing scene motion, by indicating whether its decline was too fast or too slow. The model time constant was approximated using a staircase technique. Time constants comparable to that of the Coriolis vestibular ocular reflex were obtained. Time constants could be significantly reduced by adding subject-stationary visual elements. This technique for measuring oscillopsia might be used to quantify adaptation to artificial gravity environments. In principle more complex models can be used, and applied to other types of oscillopsia such as are experienced by BPPV patients or by astronauts returning to Earth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".