Causes of Involutional Ectropion and Entropion-Age-Related Tarsal Changes Are the Key
Bibliographic record
Abstract
PURPOSE: To measure tarsal plates across various age-groups, to determine whether tarsal size changes with increasing age and whether size correlates with involutional ectropion and entropion. METHODS: Comparative, observational, case-control study design. Data were obtained for length and height of tarsus in each of the four eyelids. The data were constructed to determine: (I) right-to-left-side comparison data, (II) sex difference data, (III) age normal data, (IV) involutional entropion data, (V) involutional ectropion data. RESULTS: (I) There is no difference in tarsal dimensions between right and left sides; (II) males have larger tarsal dimensions than females; (III) tarsal plates are on average smaller in older age ranges; (IV) patients with entropion have smaller than average age-normal tarsal plates; (V) patients with ectropion have larger than average age-normal tarsal plates. CONCLUSIONS: (I) Right and left tarsal plates have equal dimensions, and involutional changes likely occur on both right and left sides equally frequently; (II) males have larger tarsal plates than females and entropion is more frequent in females and ectropion in males; (III) tarsal plates may have a general tendency to atrophy or shrink with age; this may explain why some eyelids develop entropion and others ectropion; (IV) entropion results from the mechanical effect of an atrophied or smaller than age-normal, partially or fully disinserted, tarsal plate being overcome by the normal or increased tone of the preseptal/pretarsal orbicularis muscle; (V) ectropion results from an age-normal or larger than normal tarsal plate mechanically overcoming the normal or decreased tone of the preseptal/pretarsal orbicularis muscle in combination with medial/lateral canthal tendon laxity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".