The Natural History of Spina Bifida in Children Pilot Project: Research Protocol
Bibliographic record
Abstract
BACKGROUND: Population-based empirical information to inform health care professionals working with children with spina bifida currently is lacking. Spina bifida is a highly complex condition that not only affects mobility but many additional aspects of life. We have developed a pilot project that focuses on a broad range of domains: surgeries, development and learning, nutrition and physical growth, mobility and functioning, general health, and family demographics. Specifically, we will: (1) explore the feasibility of identifying and recruiting participants using different recruitment sources, (2) test a multidisciplinary module to collect the data, (3) determine the utility of different methods of retrieving the data, and (4) summarize descriptive information on living with spina bifida. OBJECTIVE: The overall objective of the project was to provide information for a future multistate prospective study on the natural history of spina bifida. METHODS: Families with a child 3 to 6 years of age with a diagnosis of spina bifida were eligible for enrollment. Eligible families were identified through a US population-based tracking system for birth defects and from a local spina bifida clinic. RESULTS: This is an ongoing project with first results expected in 2013. CONCLUSIONS: This project, and the planned multistate follow-up project, will provide information both to health care professionals experienced in providing care to patients with spina bifida, and to those who have yet to work with this population. The long-term purpose of this project is to increase the knowledge about growing up with spina bifida and to guide health care practices by prospectively studying a cohort of children born with this condition.
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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 | 0.038 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.040 | 0.008 |
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".