Current-use pesticide exposures in remote Inuit communities
Bibliographic record
Abstract
The global use of pesticides is increasing; however, few studies have examined the exposure of current-use pesticide exposure in Inuit populations. Some current use pesticides are also capable of long-range transport, potentially increasing exposures to northern populations. The study aim was to analyse pesticide (chlorophenoxy, organophosphates, and pyrethroid pesticide) biomarker levels in pooled samples from an Inuit population in Nunavik, Quebec. Thirty pooled samples from the Qanuilirpitaa? 2017 survey (Q2017) from individuals aged 16-80 years were included. Creatinine-adjusted arithmetic (AM) were compared by sex, age, and region sub-groups, and geometric mean concentrations (GM) were compared to those in the Canadian Health Measures Survey (CHMS). Most analysed pesticide biomarkers were detected, and PNP (a metabolite of methyl and ethyl parathion), trans-DCCA (a metabolite of pyrethroids), and 3,5,6-TCP (a metabolite of chlorpyrifos) had the highest concentrations. Concentrations in Q2017 were largely similar to or less than CHMS concentrations. Although not significant, there was a general increase in 2,4-D (a chlorophenoxy biomarker), 3,5,6-TCP, 3-PBA (a metabolite of pyrethroids), and trans-DCCA with increasing age. Concentrations were also somewhat higher in females versus males, but these were not significant. Environmental exposures to current use pesticides were detected in Nunavik and concentrations were similar to or less than those in the general Canadian population. Regular monitoring of current use pesticide exposures is recommended given the increasing global use of pesticides.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".