Head shape measurement standards and cranial orthoses in the treatment of infants with deformational plagiocephaly
Bibliographic record
Abstract
This review aims to determine how head shape is measured and describes the use of orthoses in the management of deformational plagiocephaly. A systematic review was conducted and papers published in English up to and including 2006 were sourced from nine databases. After initial screening, 20 papers were included; three literature reviews and 17 original papers. Of the original papers, eight concerned the method of head shape measurement. Measurements are important in determining clinical classification and treatment modality of deformational plagiocephaly. All studies were appraised and assigned a level of evidence according to the Scottish Intercollegiate Guidelines Network. Methodological quality was inadequate. Publications involving the use of cranial orthoses used convenience samples, were not blinded, and used different measurement techniques. No comparison groups were included and participants were not randomized. Evidence suggests that conservative treatments might reduce skull deformity although the quality is poor. Clinical studies investigating the use of cranial orthoses reported beneficial effects. Further research is required to identify the efficacy of cranial orthoses in the treatment of deformational plagiocephaly based on a standardized measurement technique to facilitate classification of 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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".