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Record W2167864976 · doi:10.1039/c4em00674g

Iodine status of Eeyou Istchee community members of northern Quebec, Canada, and potential sources

2015· article· en· W2167864976 on OpenAlexafffundabout
Benita Y. Tam, Leonard J. S. Tsuji, Ian Martin, Eric N. Liberda, Pierre Ayotte, Suzanne Côté, Éric Dewailly, Evert Nieboer

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2015
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsMcMaster UniversityInstitut National de Santé Publique du QuébecCentre hospitalier universitaire de QuébecToronto Public HealthThe Scarborough HospitalRegional Municipality of WaterlooToronto Metropolitan UniversityUniversity of TorontoUniversity of Waterloo
FundersCree Board of Health and Social Services of James Bay
KeywordsIodineIndigenousCreatinineGeographyEnvironmental healthMedicineChemistryInternal medicineEcologyBiology

Abstract

fetched live from OpenAlex

A multi community environment-and-health study among six of the nine communities of Eeyou Istchee in northern Quebec, Canada provided greater insight into iodine intake levels among these Cree First Nation communities. Using data from this large population-based study, descriptive statistics of measured urinary iodine concentrations (UICs) and iodine-creatinine ratios (stratified by age, sex, community of residence, and water consumption) were calculated, and the associations between independent variables and iodine concentration measures were examined through a general linear model. Traditional food consumption contributions were examined through Pearson partial correlation tests and linear regression analyses; and the importance of water sources through ANOVA. Generally speaking, urinary iodine levels of Eeyou Istchee community members were within the adequate range set out by the World Health Organization, though sex and community differences existed. However, men in one community were considered to be at risk of iodine deficiency. Older participants had significantly higher mean iodine-creatinine ratios than younger participants (15-39 years = 90.50 μmol mol(-1); >39 years = 124.52 μmol mol(-1)), and consumption of beaver (Castor canadensis) meat, melted snow and ice, and bottled water were predictive of higher iodine excretion. It is concluded that using both urinary iodine indicators can be helpful in identifying subgroups at greater risk of iodine deficiency.

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 score0.025
Threshold uncertainty score0.411

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 studies0.0000.001
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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Citations5
Published2015
Admission routes3
Has abstractyes

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