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Record W2073988436 · doi:10.3200/aeoh.64.1.29-45

Risk of Abortion and Stillbirth in Cow-Calf Herds Exposed to the Oil and Gas Industry in Western Canada

2009· article· en· W2073988436 on OpenAlexaffabout
Cheryl Waldner

Bibliographic record

VenueArchives of Environmental & Occupational Health · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsIce calvingHerdAbortionHydrogen sulfideAnimal scienceEnvironmental scienceEnvironmental chemistryMedicinePregnancyChemistrySulfurBiologyLactationOrganic chemistry

Abstract

fetched live from OpenAlex

To investigate the associations between emissions from oil and gas field facilities and fetal survival, researchers followed more than 28,000 beef cows from the beginning of the breeding season through calving. They prospectively measured exposure to sulfur dioxide, hydrogen sulfide, and volatile organic compounds and linked them to the location of individual cattle; they used the density of oil and gas well sites surrounding each pasture as an alternate measure of exposure. The researchers measured the risks of abortion and stillbirth in 203 cow-calf herds for the 2002 calving season, as well as animal and herd-management factors known or suspected to affect these parameters. Using mixed models to adjust for clustering by herd and after accounting for other known risk factors, they examined the associations between exposure to sulfur dioxide, volatile organic compounds measured as benzene and toluene, hydrogen sulfide, and well-site density, and the risks of abortion and stillbirth. There was no evidence across the measured range of exposures that emissions of sulfur dioxide, hydrogen sulfide, volatile organic compounds measured as benzene or toluene, or well-site density increased the risk of either abortion or stillbirth in these beef herds.

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 score0.123
Threshold uncertainty score0.930

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 head0.006
GPT teacher head0.226
Teacher spread0.220 · 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

Citations13
Published2009
Admission routes2
Has abstractyes

Explore more

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