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Record W2916922551 · doi:10.1038/s41598-019-38856-5

Prevalence of Fetal Alcohol Exposure by Analysis of Meconium Fatty Acid Ethyl Esters; A National Canadian Study

2019· article· en· W2916922551 on OpenAlexafffundabout
Kaitlyn Delano, Gideon Koren, Martin Zack, Bhushan Kapur

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsWestern UniversityUniversity of Toronto
FundersCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsMeconiumBiomarkerMedicineAlcoholFetusGas chromatography–mass spectrometryObstetricsFetal alcoholPregnancyEnvironmental healthPhysiologyChromatographyChemistryMass spectrometryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Our study aimed to estimate the prevalence of heavy fetal alcohol exposure through the analysis of meconium FAEEs as an objective biomarker of fetal exposure. We conducted a study on meconium samples collected nationwide through the Maternal-Infant Research on Environmental Chemicals (MIREC) Study Group. FAEE in meconium was quantified by an established headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (SPME GC-MS). Out of 1315 samples collected in 10 Canadian obstetric units coast to coast between 2008-2011, the estimated prevalence of positive meconium FAEE ranged between 1.16% and 2.40%, translating into at least 1800 new cases of FASD in Canada each year. Positive maternal self- reports of heavy alcohol use were tenfold lower (0.24%). Use of meconium FAEE revealed tenfold more cases of heavy exposure to maternal drinking than did maternal reports. The use of objective measures of maternal alcohol exposure is critical in accurately estimating risks and in monitoring effective prevention of FASD.

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

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.013
GPT teacher head0.268
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2019
Admission routes3
Has abstractyes

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