Fetal ethanol exposure and meconium analysis of fatty acid ethyl esters in neonatal screening: The first Canadian population-based study
Bibliographic record
Abstract
Challenges in identifying children exposed prenatally to ethanol necessitate the development of a biomarker to screen for neonates at risk for Fetal Alcohol Spectrum Disorder. Meconium fatty acid ethyl esters (FAEE), products of non-oxidative ethanol metabolism, have been established as a novel biomarker of fetal ethanol exposure. This study is the first application of this test to a regional neonatal population in Canada. Six-hundred eighty-two anonymously collected meconium samples were analyzed by GC-FID and GC-MS. Ethyl myristate, ethyl palmitate, ethyl palmitoleate, ethyl stearate, ethyl oleate, ethyl linolate, ethyl linolenate, and ethyl arachidonate were measured. GC-FID screening produced a sensitivity of 100% and specificity of 97% with positive and negative predictive values of 45.9% and 100%, respectively, for successful GC-MS confirmation. FAEE analysis detected 5-fold more ethanol-exposed pregnancies than standard post-partum screening in this population, demonstrating a 2.5% prevalence of fetal ethanol exposure, consistent with CDC estimates of 'frequent' prenatal drinking.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".