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Record W7074232184

Risk of pregnancy-related hypertension within 5 years of exposure to drinking water contaminated with Escherichia coli O157:H7

2010· article· en· W7074232184 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsBlood pressureAsymptomaticGestationPregnancyGestational hypertensionIncidence (geometry)Chronic hypertensionConfidence interval
DOInot available

Abstract

fetched live from OpenAlex

The authors evaluated the risk for pregnancy-related hypertension among previously healthy women who conceived within 5 years of exposure to drinking water contaminated with Escherichia coli O157.H7 in Walkerton, Canada (2000). Chronic hypertension was defined as systolic/diastolic blood pressure ≥140/90 mm Hg before 20 weeks gestation; gestational hypertension was defined as new onset systolic/diastolic blood pressure ≥140/90 mm Hg ≥20 weeks gestation. The incidence of hypertension was compared between women who were asymptomatic during the outbreak to those who experienced acute gastroenteritis. Blood pressure data were available for 135 of 148 eligible pregnancies. The adjusted relative risks for chronic and gestational hypertension were 1.5 (95% confidence interval [CI]: 0.3-7.7) and 1.0 (95% CI: 0.4-2.5), respectively. Mean arterial pressure before 20 weeks gestation was 2.7 mm Hg higher in women who had acute gastroenteritis (95% CI: 0.05-5.4). A trend toward higher chronic hypertension and mean arterial pressure in early pregnancy was observed among women who experienced gastroenteritis after exposure to bacterially-contaminated drinking water. © 2010 Wiley Periodicals, Inc.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0010.000
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 head0.017
GPT teacher head0.229
Teacher spread0.212 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2010
Admission routes1
Has abstractyes

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