The effects of preterm birth on visual development
Bibliographic record
Abstract
Children born very preterm are at a greater risk of abnormal visual and neurological development when compared to children born at full term. Preterm birth is associated with retinopathy of prematurity (a proliferative retinal vascular disease) and can also affect the development of brain structures associated with post-retinal processing of visual information. Visual deficits common in children born preterm, such as reduced visual acuity, strabismus, abnormal stereopsis and refractive error, are likely to be detected through childhood vision screening programs, ophthalmological follow-up or optometric care. However, routine screening may not detect other vision problems, such as reduced visual fields, impaired contrast sensitivity and deficits in cortical visual processing, that may occur in children born preterm. For example, visual functions associated with the dorsal visual processing stream, such as global motion perception and visuomotor integration, may be impaired by preterm birth. These impairments can continue into adolescence and adulthood and may contribute to the difficulties in learning (particularly reading and mathematics), attention, behaviour and cognition that some children born preterm experience. Improvements in understanding the mechanisms by which preterm birth affects vision will inform future screening and interventions for children born preterm.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".