Cohort profile: health effects monitoring programme in Ndilǫ, Dettah and Yellowknife (YKHEMP)
Bibliographic record
Abstract
PURPOSE: The Yellowknife Health Effects Monitoring Programme (YKHEMP) was established to examine the relationship of exposure to arsenic and other chemicals of potential concern such as antimony, cadmium, lead, manganese and vanadium and health outcomes. PARTICIPANTS: A total of 2037 individuals were recruited, including children (age 3-19) and adults (age 20+), residing in Dettah, Ndilǫ and Yellowknife, in the Northwest Territories, Canada, in two waves in Fall 2017 and Spring 2018. In Yellowknife, there were 891 (675 adults, 216 children), randomly selected participants with a participation rate of 64%. In addition, we also recruited a total of 875 (669 adults, 206 children) volunteer participants. A total of 225 (137 adults, 88 children) of the Yellowknives Dene First Nation (YKDFN), and 46 (33 adults, 13 children) of the North Slave Métis Alliance participated in the study. Each participant answered a lifestyle questionnaire as well as provided toenail clippings and urine for contaminant testing and saliva samples for testing of genetic polymorphisms associated with arsenic metabolism. Participants also provided consent to have their medical records reviewed by the research team for the past 5 years to allow for the investigation between exposure and health outcomes. FINDINGS TO DATE: The adult YKHEMP participants had lower urinary total arsenic but the children had higher inorganic arsenic than the general Canadian population. There was no difference in urinary total arsenic concentrations between adults and children, however, urinary inorganic arsenic concentrations were generally higher in children than in adults in all four YKHEMP sampling groups. The adult YKDFN participants had lower urinary total arsenic and inorganic arsenic concentrations compared with the random selected and volunteer participants. FUTURE PLANS: YKHEMP is designed as a prospective cohort study; the children participants will be re-examined in 2022 and both adult and children participants in 2027.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".