Development in spina bifida: Neurobiological and environmental factors
Bibliographic record
Abstract
Introduction Spina bifida myelomeningocele (SBM) is one of the world's most common disabling birth defects, yet, until recently, its genetic, neural, and cognitive phenotypes have been less systematically investigated than those of other neurogenetic disorders, including several of those featured in this volume. This chapter describes the findings from a large-scale multi-site study of more than 260 children with SBM between the ages of 7 and 16 years and over 160 children with SBM and their typically developing peers followed from infancy into school age that involves collaboration between the University of Texas Health Science Center at Houston, the University of Houston, and the Toronto Hospital for Sick Children. The material is organized as follows: (1) What is SBM?; (2) The SBM genotype; (3) Relations between genotype and physical and neural phenotypes; (4) The SBM behavioral phenotype in relation to lesion level and environmental factors: intelligence, academic skills, and adaptive function; (5) Theoretical questions about typical and atypical development generated from studies of the SBM phenotype; (6) Longitudinal development in SBM from infancy through childhood and into adult life; and (7) Clinical care and intervention issues. What is SBM? SBM, a neural tube defect that affects the development of both spine and brain, arises in the third to fourth week of embryogenesis, and results in a failure of neural tube closure. The physical phenotype includes paraplegia of the lower limbs and neurogenic bladder and bowel function (Charney, 1992).
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".