P.080 Head circumference values among Inuit children in Nunavut, Canada: a retrospective cohort study
Bibliographic record
Abstract
Background: Inuit children have been observed to have high rates of macrocephaly, which leads to burdensome travel for medical evaluation, often with no pathology identified. Given reports that WHO growth charts may not reflect all populations, we compared head circumference (HC) measurements in a cohort of Inuit children with the WHO charts. Methods: We extracted HC data from a retrospective cohort study where, with Inuit partnership, we reviewed medical records of Inuit children, born between 2010-2013, and residing in Nunavut. We excluded children with preterm birth, documented neurologic/genetic disease, and most congenital anomalies. We compared HC values with the 2007 WHO charts. Results: We analyzed records of 1960 Inuit children (8866 data points). Most data were from ages 0-36 months. At all age points, the cohort had statistically significantly larger HC than WHO medians. At age 12 months, median HC were 1.3 cm and 1.5 cm larger for male and female Inuit children. Using WHO growth curves, macrocephaly was overdiagnosed and microcephaly underdiagnosed. Conclusions: Our results support the observation that Inuit children from Nunavut have larger HCs, and use of the WHO charts may lead to overdiagnosis of macrocephaly and underdiagnosis of microcephaly. Population specific growth curves for Inuit children should be considered.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".