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Record W2400810974

Cadmium levels and sources of exposure among Canadian adults.

2016· article· en· W2400810974 on OpenAlexaffabout
Rochelle Garner, Patrick Levallois

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsInstitut National de Santé Publique du QuébecStatistics Canada
Fundersnot available
KeywordsCadmiumCADMIUM EXPOSUREEnvironmental healthMedicineDemographyPhysiologyChemistry
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Cadmium is a heavy metal found naturally in the environment that has been associated with negative health outcomes. The present study examines levels of blood cadmium (BCd), urinary cadmium (UCd), and the main sources of cadmium exposure among Canadians aged 20 to 79. DATA AND METHODS: The data are from cycles 1 (2007 to 2009) and 2 (2009 to 2011) of the Canadian Health Measures Survey (CHMS), including measures of BCd and UCd, markers of smoking status (self-reported and second-hand smoke exposure), and self-reported consumption of foods known to be high in cadmium. The relationship between sources of exposure and cadmium levels was examined descriptively. The magnitude of the contribution of different exposure sources was examined in regression models. RESULTS: Age and smoking status were the greatest contributors to BCd and UCd: older people and current smokers had the highest cadmium levels. Dietary exposure, while significant, was a modest contributor overall, but a more important source of cadmium among never-smokers. INTERPRETATION: Smoking was the greatest contributor to cadmium levels among Canadians aged 20 to 79. Dietary differences explained a small percentage of variation in cadmium levels.

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 score0.159
Threshold uncertainty score0.908

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 head0.172
Teacher spread0.160 · 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

Citations88
Published2016
Admission routes2
Has abstractyes

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