Spontaneous Blink Rates in Children During Different Types of Eye Movements
Bibliographic record
Abstract
INTRODUCTION: The spontaneous blink rate (SBR) is variable in humans. It increases rapidly during childhood before reaching a plateau in adulthood at 10-20 blinks/minute. Our aim was to compare the SBR during different visual tasks in children. METHODS: Thirty-nine healthy participants (mean age(SD):13.6(3.5)years, M=21), made horizontal and vertical visually-guided saccades, tracked a horizontal and vertical target, performed horizontal and vertical active sinusoidal head rotations in light and darkness while looking straight ahead (VOR task) or fixated straight ahead and in four directions of gaze. The eyes of each participant were videotaped and reviewed twice to determine the SBR. Parametric and non-parametric tests were used to analyze the data. RESULTS: The median SBR during fixation straight ahead was seven blinks/minute, which was similar to the SBR during horizontal saccades and horizontal smooth pursuit tasks. The median SBR during vertical smooth pursuit and vertical saccades were significantly lower than during fixation (p≤0.042). The median SBR during the VOR task in light and horizontal VOR in darkness were significantly higher than during fixation (p=0.019-0.024). CONCLUSIONS: The median SBR during visual fixation was lower than that reported previously in 5-14 years-old children during rest or 11-20 years-old subjects during quiet conversation. The median SBR was even lower during vertical smooth pursuit and saccades tasks. This may be due to differences in concentration required for visual fixation in general and vertical visual tasks more specifically. The higher SBR during the VOR may be due to drying of the eyes during head shaking.
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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 | 0.003 |
| 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".