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Record W3008979599 · doi:10.1289/ehp5621

Gestational Exposures to Phthalates and Folic Acid, and Autistic Traits in Canadian Children

2020· article· en· W3008979599 on OpenAlexafffundabout
Youssef Oulhote, Bruce P. Lanphear, Joseph M. Braun, Glenys M. Webster, Tye E. Arbuckle, Taylor Etzel, Nadine Forget‐Dubois, Jean R. Séguin, Maryse F. Bouchard, Amanda J MacFarlane, Emmanuel Ouellet, William D. Fraser, Gina Muckle

Bibliographic record

VenueEnvironmental Health Perspectives · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsUniversité de SherbrookeCentre Hospitalier Universitaire Sainte-JustineBC Children's HospitalUniversité de MontréalUniversité LavalChild and Family Research InstituteHealth CanadaSimon Fraser UniversityCentre hospitalier universitaire de Québec
FundersNational Institute of Environmental Health SciencesCanadian Institutes of Health Research
KeywordsBiostatisticsPublic healthEpidemiologyLibrary scienceGerontologyMedicineFamily medicineSociologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: The etiology of autism spectrum disorder is poorly understood. Few studies have investigated the link between endocrine-disrupting chemicals and autistic traits. We examined the relationship between gestational phthalates and autistic traits in 3- to 4-y-old Canadian children. We also investigated potential effect modification by sex and folic acid supplementation. METHODS: -scores with a doubling in phthalate concentrations in 510 children with complete data. RESULTS: ). CONCLUSIONS: Higher gestational concentrations of some phthalate metabolites were associated with higher scores of autistic traits as measured by the SRS-2 in boys, but not girls; these small size effects were mitigated by first trimester-of-pregnancy folic acid supplementation. https://doi.org/10.1289/EHP5621.

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 score0.029
Threshold uncertainty score0.962

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.303
Teacher spread0.295 · 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

Citations108
Published2020
Admission routes3
Has abstractyes

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