The Relationship Between Periventricular Brain Injury and Deficits in Visual Processing Among Extremely-Low-Birthweight (<1000 g) Children
Bibliographic record
Abstract
OBJECTIVE: To examine the relationship between neonatal, periventricular brain damage and visuomotor performance in extremely-low-birthweight (ELBW) children of normal intelligence whose birthweights were appropriate for gestational age (AGA). METHODS: Seventy-eight ELBW and 23 control children, all six years of age, completed two "motor-free" tests of visual spatial ability and three tests requiring visuomotor control. RESULTS: Full-term control children outperformed ELBW children with periventricular brain damage on all three tests requiring visuomotor guidance. No group differences were found on two "motor-free" tests of visual spatial ability. ELBW children without periventricular brain damage performed in a manner indistinguishable from controls on all tests included in this study. CONCLUSIONS: The findings indicate that the presence and severity of periventricular brain injury are important factors to consider in predicting visuomotor development in ELBW children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".