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Record W2809770061 · doi:10.3390/challe9020026

Industrial Developmental Toxicants and Congenital Heart Disease in Urban and Rural Alberta, Canada

2018· article· en· W2809770061 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueChallenges · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsAlberta Children's HospitalStollery Children's HospitalUniversity of CalgaryWomen and Children’s Health Research InstituteUniversity of Alberta
FundersFaculty of Medicine and Dentistry, University of AlbertaUniversity of AlbertaCanadian Institutes of Health ResearchWomen and Children's Health Research InstituteChildren's Health Research InstituteNatural Sciences and Engineering Research Council of CanadaAlberta Health Services
KeywordsAerodynamic diameterPoisson regressionRelative riskNitrogen dioxideSocioeconomic statusEnvironmental healthDemographyHeart diseaseEtiologyMedicineAir pollutionPoisson distributionAir pollutantsConfidence intervalToxicologyGeographyInternal medicineStatisticsMathematicsBiologyPopulationMeteorologyEcology

Abstract

fetched live from OpenAlex

The etiology of congenital heart defects (CHD) is not known for many affected patients. In the present study, we examined the association between industrial emissions and CHD in urban and rural Alberta. We acquired the emissions data reported in the Canadian National Pollutant Release Inventory (n = 18) and identified CHD patients born in Alberta from 2003–2010 (n = 2413). We identified three groups of emissions after principal component analysis: Groups 1, 2, and 3. The distribution of exposure to the postal codes with births was determined using an inverse distance weighted approach. Poisson or negative binomial regression models helped estimate associations (relative risk (RR), 95% Confidence Intervals (CI)) adjusted for socioeconomic status and two criteria pollutants: nitrogen dioxide and particulate matter with a mean aerodynamic diameter of ≤2.5 micrometers. The adjusted RR in urban settings was 1.8 (95% CI: 1.5, 2.3) for Group 1 and 1.4 (95% CI: 1.3, 1.6) for both Groups 2 and 3. In rural postal codes, Groups 1 and 3 emissions had a RR of 2.6 (95% CI: 1.03, 7). Associations were only observed in postal codes with the highest levels of emissions and maps demonstrated that regions with very high exposures were sparse.

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.

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 score0.492
Threshold uncertainty score0.569

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 head0.061
GPT teacher head0.270
Teacher spread0.209 · 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