A clinically oriented video-based system for quantification of eyelid movements
Bibliographic record
Abstract
A field-worthy system was developed to quantify the eyelid movements in clinical sites. The system consists of a home-use charge-coupled device video camera, a processing unit, and a personal computer. A white marker of 4-mm diameter and 30-mg weight is attached to the lower margin of the upper eyelid. The processing unit automatically detects the vertical displacement of the upper edge of the marker. One marker is attached to each eye so that the movements of the both eyelids are measured with one camera simultaneously. The measurement error of the system was evaluated in experiments on eight healthy subjects and eight patients with eyelid paralysis. The mean of the absolute error of peak amplitudes occurring in 2 min was 0.81 mm, with the worst error being +1.7 mm. The reproducibility of the mean peak amplitude measured on five consecutive days was within 1 mm. The mean peak amplitudes of both eyes were measured preoperatively and postoperatively for approximately three months for three patients who were operated on to remove vestibular schwannoma. The results demonstrated basic clinical utility of the system.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".