MétaCan
Menu
Back to cohort

Abstract 14197: Industrial Developmental Toxicant Emissions and Congenital Heart Disease in Urban and Rural Alberta, Canada

2015· article· en· W4395039474 on OpenAlexaffabout
Deliwe P. Ngwezi, Lisa K. Hornberger, Jesús Serrano-Lomelin, Deborah Fruitman, Álvaro Osornio-Vargas

Bibliographic record

VenueCirculation · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineToxicantHeart diseaseEnvironmental healthDiseaseCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Background: We have previously demonstrated a downward temporal association between mixtures of organic solvents released into air from industrial sources and congenital heart disease (CHD) in Alberta. Hypothesis: In the current study we hypothesized that the downward temporal associations between developmental toxicants (DTs) and CHD would have a different industrial sector participation in the urban and rural areas of Alberta. Methods: We extracted yearly emissions of DTs (tonnes) from Canada’s National Pollutant Release Inventory as released to air between 2003-2010. We identified at the postal code level, all CHD cases born between 2004-2011 through our provincial-wide echocardiography database. We calculated yearly urban and rural CHD crude rates. Urban and rural were defined according to Forward Sortation Areas. Principal Component Analysis was undertaken to reduce the dimensionality of the number of DTs and the yearly solution was applied to rural and urban areas to test correlations with corresponding yearly CHD rates. Results: Three principal components (PCs) were identified: PC1 consisted of a mixture of organics and gases, PC2 consisted of a mixture of organics only and PC3 consisted of metals. There were strong positive correlations between CHD rates and urban PC1 emissions from mining and manufacturing, (r=0.76, p=0.03; 0.74, p=0.04); whereas in rural areas, PC1 emissions from mining and utilities and PC2 emissions from mining and manufacturing were associated with rates of CHD, (r=0.71, p=0.05; r=0.74, p=0.04 and r=0.86, p=0.01; r=0.74, p=0.04, respectively). PC3 showed no positive correlations (Table 1). Conclusions: CHD rates are consistently strongly correlated with mixtures of organic compounds and gases, with different patterns of chemicals and sectors involved in the urban and rural settings. This provides an opportunity to further investigate spatial correlations between DTs and CHD rates at a higher resolution scale.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.011
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.235
Teacher spread0.207 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueCirculationSame topicHealth, Environment, Cognitive AgingFrench-language works237,207