Modeling the Inuit diet to minimize contaminant while maintaining nutrient intakes
Bibliographic record
Abstract
The Arctic environment is changing rapidly. The purposes of this study were: (1) to predict the possible changes of diet composition and the subsequent changes in nutrient intakes as a result of environmental changes; (2) to explore the possibility of minimizing the contaminant exposure while maintaining the energy and nutrient intakes using liner modeling. It was found that a decrease of 10% or 50% of caribou or ringed seal will result in decreases for many key nutrients such as protein, zinc, and iron. It is theoretically feasible to minimize each contaminant intake while maintaining energy and nutrients at the levels of the CINE dietary survey in 2000 for Inuit in the Inuvialuit, Kitikmeot, and Kivalliq regions. However, it is theoretically infeasible for Inuit in the Labrador and Baffin regions under other hypothetical conditions. The modeling results would be useful for Inuit to make informed food choice decisions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".