Ethnic variations in birthweight percentiles in Kuwait
Bibliographic record
Abstract
The objectives of this retrospective study were to assess the effect of ethnicity on birthweight percentiles and to compare ethnic-specific percentiles with other references. Analysis was made of 35 768 singleton live births from 22 to 44 completed weeks of gestation at two major obstetric hospitals in Kuwait, after exclusion of data with inaccurate gestational age, major congenital abnormalities, stillbirths, and outlying birthweights. The population included four major ethnic groups: Gulf Arabs, Mediterranean Arabs, Egyptians, and a group combining Indians and Southeast Asians. Total population and ethnic-specific smoothed birthweight percentiles according to gestational age were developed. Indians-Asians had the smallest birthweights, the highest prevalence of small-for-gestational-age (SGA) birthweights and the lowest prevalence of large-for-gestational-age (LGA) birthweights. On the contrary, Egyptians had the largest birthweights, the lowest prevalence of SGA birthweights and the highest prevalence of LGA birthweights. Plotting our birthweights on a reference from Canada resulted in a low prediction rate for SGA and a low sensitivity in identifying LGA of all ethnic groups. We conclude that interpretation of fetal growth and birthweight should involve locally derived and ethnically specific percentiles based on accurately calculated gestational age.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".