A cross‐sectional survey of 5‐year‐old children with non‐syndromic unilateral cleft lip and palate: the Cleft Care <scp>UK</scp> study. Part 1: background and methodology
Bibliographic record
Abstract
OBJECTIVES: We describe the methodology for a major study investigating the impact of reconfigured cleft care in the United Kingdom (UK) 15 years after an initial survey, detailed in the Clinical Standards Advisory Group (CSAG) report in 1998, had informed government recommendations on centralization. SETTING AND SAMPLE POPULATION: This is a UK multicentre cross-sectional study of 5-year-olds born with non-syndromic unilateral cleft lip and palate. Children born between 1 April 2005 and 31 March 2007 were seen in cleft centre audit clinics. MATERIALS AND METHODS: Consent was obtained for the collection of routine clinical measures (speech recordings, hearing, photographs, models, oral health, psychosocial factors) and anthropometric measures (height, weight, head circumference). The methodology for each clinical measure followed those of the earlier survey as closely as possible. RESULTS: We identified 359 eligible children and recruited 268 (74.7%) to the study. Eleven separate records for each child were collected at the audit clinics. In total, 2666 (90.4%) were collected from a potential 2948 records. The response rates for the self-reported questionnaires, completed at home, were 52.6% for the Health and Lifestyle Questionnaire and 52.2% for the Satisfaction with Service Questionnaire. CONCLUSIONS: Response rates and measures were similar to those achieved in the previous survey. There are practical, administrative and methodological challenges in repeating cross-sectional surveys 15 years apart and producing comparable data.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".