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Record W2042348185 · doi:10.1289/ehp.01109957

Determinants of polychlorinated biphenyls and methylmercury exposure in inuit women of childbearing age.

2001· article· en· W2042348185 on OpenAlexaffabout
Gina Muckle, Pierre Ayotte, Éric Dewailly, Sandra W. Jacobson, Joseph L. Jacobson

Bibliographic record

VenueEnvironmental Health Perspectives · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversité Laval
FundersNational Institute of Environmental Health Sciences
KeywordsBeluga WhaleMethylmercuryPregnancyBelugaEnvironmental healthMercury (programming language)Socioeconomic statusMedicineFish consumptionPhysiologySeleniumFish <Actinopterygii>PopulationBiologyEcologyFisheryChemistry

Abstract

fetched live from OpenAlex

The objectives of this study were to to identify maternal characteristics associated with traditional food consumption and to examine food items associated with polychlorinated biphenyls (PCBs) and mercury body burden in pregnant Inuit women from Northern Québec. We interviewed women from three communities at mid-pregnancy and at 1 and 11 months postpartum. We measured PCBs, Hg, and selenium in maternal blood; Hg was also measured in maternal hair. The women reported eating significant amounts of fish, beluga muktuk/fat, seal meat, and seal fat. Although consumption of fish and seal was associated with lower socioeconomic status, consumption of beluga whale was uniform across strata. Fish and seal meat consumption was associated with increased Hg concentrations in hair. Traditional food intake during pregnancy was unrelated to PCB body burden, which is more a function of lifetime consumption. This study corroborated previous findings relating marine mammal and fish consumption to increased Hg and selenium body burden. Despite widespread knowledge regarding the presence of these contaminants in traditional foods, a large proportion of Inuit women increased their consumption of these foods during pregnancy, primarily because of pregnancy-related changes in food preferences and the belief that these foods are beneficial during pregnancy.

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)0.000
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 score0.104
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.287
Teacher spread0.272 · 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

Citations107
Published2001
Admission routes2
Has abstractyes

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