MétaCan
Menu
Back to cohort

Soil ingestion rate determination in a rural population of Alberta, Canada practicing a wilderness lifestyle

2013· article· en· W2047055261 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

VenueThe Science of The Total Environment · 2013
Typearticle
Languageen
FieldHealth Professions
TopicRadioactivity and Radon Measurements
Canadian institutionsUniversity of Ottawa
FundersHealth CanadaHeartland Health Research Alliance
KeywordsIngestionEnvironmental sciencePopulationEnvironmental healthMedicine

Abstract

fetched live from OpenAlex

The inadvertent ingestion of contaminated soil can be a major pathway for chemical exposure to humans. Few studies to date have quantified soil ingestion rates to develop exposure estimates for human health risk assessments (HHRA), and almost all of those were for children in suburban/urban environments. Here we employed a quantitative mass balance tracer approach on a rural population practicing outdoor activities to estimate inadvertent soil ingestion. This study followed 9 subjects over a 13 day period in Cold Lake, Alberta, near the largest in situ thermal heavy oil (bitumen) extraction operation in the world. The mean soil ingestion rate in this study using Al Ce, La, and Si tracers was 32 mg d(-1), with a 90th percentile of 152 mg d(-1) and median soil ingestion rate of 18 mg d(-1). These soil ingestion values are greater than the standard recommended soil ingestion rates for HHRA from Health Canada, and are similar to soil ingestion estimates found in the only other study on a rural population.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.021
GPT teacher head0.287
Teacher spread0.266 · 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