Axial Length and Associated Factors in Children: The Shandong Children Eye Study
Bibliographic record
Abstract
PURPOSE: To investigate ocular axial length (AL) in Chinese children. METHODS: The Shandong Children Eye Study included 6,364 children aged 4-18 years. RESULTS: Longer AL (mean 23.45 ± 1.20 mm, range 18.80-28.59 mm) was associated (multivariate analysis; correlation coefficient r2: 0.61) with older age (p < 0.001, standardized correlation coefficient β = 0.35, unstandardized regression coefficient B = 0.13, 95% confidence interval [CI] 0.12, 0.15), male gender (p < 0.001, β = -0.24, B = -0.10, 95% CI -0.29, -0.19), urban region (p < 0.001, β = 0.10, B = 0.25, 95% CI 0.20, 0.31), body height (p < 0.001, β = 0.22, B = 0.02, 95% CI 0.01, 0.02), maternal education (p < 0.001, β = 0.07, B = 0.07, 95% CI 0.05, 0.10), paternal myopia (p < 0.001, β = 0.09, B = 0.26, 95% CI 0.20, 0.33), maternal myopia (p < 0.001, β = 0.08, B = 0.23, 95% CI 0.17, 0.30), more time spent indoors reading/writing (p < 0.001, β = 0.05, B = 0.03, 95% CI 0.02, 0.04), less time spent outdoors (p = 0.005, β = -0.03, B = -0.01, 95% CI -0.02, -0.003), longer corneal curvature radius (p < 0.001, β = 0.36, B = 1.63, 95% CI 1.53, 1.74) and higher intraocular pressure (p = 0.008, β = 0.03, B = 0.01, 95% CI 0.004, 0.02). High axial myopia (AL ≥26.0 mm) present in 202 children (3.4 ± 0.2%, 95% CI 2.92, 3.84) was associated with less time spent outdoors (p = 0.002, odds ratio 0.92, 95% CI 0.87, 0.97) in multivariate analysis. CONCLUSIONS: In children in the less developed Eastern Chinese province of Shandong, the prevalence of high axial myopia was >10% among 16-year-olds. A modifiable factor associated with higher prevalence of high axial myopia was less time spent outdoors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".