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Record W2556739107 · doi:10.1136/oemed-2016-103956

Elevated ambient temperatures and risk of neural tube defects

2016· article· en· W2556739107 on OpenAlexafffundabout
Nathalie Auger, William D. Fraser, Laura Arbour, Marianne Bilodeau‐Bertrand, Tom Kosatsky

Bibliographic record

VenueOccupational and Environmental Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsBC Centre for Disease ControlUniversity of British ColumbiaUniversité de SherbrookeUniversité de MontréalInstitut National de Santé Publique du Québec
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsNeural tubeSpina bifidaMedicineNeural tube defectSurgeryBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: The association between ambient heat and neural tube defects has received limited attention, despite imminent climate warming this century. We sought to determine the relationship between elevated outdoor temperatures during neurogenesis and risk of neural tube defects. METHODS: We carried out a retrospective cohort study of 887 710 fetuses between 3 and 4 weeks postconception from the months of April through September for 1988-2012 in Quebec, Canada. The exposure was maximum daily temperature and the outcome presence of neural tube defects at delivery. We estimated prevalence ratios (PR) and 95% CIs for the association between maximum temperature and neural tube defects in log-binomial regression models adjusted for maternal characteristics. RESULTS: Relative to 20°C, exposure to temperatures of 30°C was associated with risk of neural tube defects on day 5 (PR 1.56, 95% CI 1.04 to 2.35) and day 6 (PR 1.49, 95% CI 1.00 to 2.21) of the 4th week postconception, during the time of neural tube closure. The trend was apparent for spina bifida and anencephalus/encephalocoele, the main subtypes of neural tube defects. Temperature during the 3rd week postconception was not associated with neural tube defects. CONCLUSIONS: Elevated ambient temperatures may be weakly associated with risk of neural tube defects during tube closure.

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 score0.355
Threshold uncertainty score0.356

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 head0.012
GPT teacher head0.260
Teacher spread0.248 · 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

Citations39
Published2016
Admission routes3
Has abstractyes

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