Mathematics skills in good readers with hydrocephalus
Bibliographic record
Abstract
Children with hydrocephalus have poor math skills. We investigated the nature of their arithmetic computation errors by comparing written subtraction errors in good readers with hydrocephalus, typically developing good readers of the same age, and younger children matched for math level to the children with hydrocephalus. Children with hydrocephalus made more procedural errors (although not more fact retrieval or visual-spatial errors) than age-matched controls; they made the same number of procedural errors as younger, math-level matched children. We also investigated a broad range of math abilities, and found that children with hydrocephalus performed more poorly than age-matched controls on tests of geometry and applied math skills such as estimation and problem solving. Computation deficits in children with hydrocephalus reflect delayed development of procedural knowledge. Problems in specific math domains such as geometry and applied math, were associated with deficits in constituent cognitive skills such as visual spatial competence, memory, and general knowledge.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".