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Record W4402534706 · doi:10.1038/s41390-024-03547-z

Development and child health in a world of synthetic chemicals

2024· review· en· W4402534706 on OpenAlexafffund
Jessica L. Wager, Jennifer Thompson

Bibliographic record

VenuePediatric Research · 2024
Typereview
Languageen
FieldEnvironmental Science
TopicEffects and risks of endocrine disrupting chemicals
Canadian institutionsLibin Cardiovascular Institute of AlbertaAlberta Children's HospitalUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaHeart and Stroke Foundation of Canada
KeywordsEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

Chemical pollution is one of today's most significant threats to the developmental potential of children worldwide. Maternal exposure to toxicants can perturb sensitive windows of fetal development, indirectly through promoting antenatal disorders, abnormal placental adaptation, or directly through maternal-fetal transport. Current evidence clearly shows that persistent organic chemicals promote hypertensive disorders of pregnancy, placental abnormalities, and fetal growth restriction, whereas findings are less consistent for phthalates and bisphenols. Prospective birth cohorts strongly support a link between adverse neurodevelopmental outcomes and prenatal exposure to flame retardants and organophosphate pesticides. Emerging evidence reveals a potential association between in utero exposure to bisphenols and childhood behavioral disorders, while childhood metabolic health is more consistently associated with postnatal exposure to phthalates and bisphenols. IMPACT: Synthesizes emerging evidence linking modern forms of chemical pollution to antenatal disorders, fetal growth restriction and childhood disorders. Highlights potential developmental impacts of emerging pollutants of concern now ubiquitous in our environment but without regulatory restrictions.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.659

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 science0.0000.001
Research integrity0.0000.001
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 head0.075
GPT teacher head0.484
Teacher spread0.410 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2024
Admission routes2
Has abstractyes

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