Organic nutrients and contaminants in subsistence species of Alaska: Concentrations and relationship to food preparation method
Bibliographic record
Abstract
OBJECTIVES: To determine nutrient and contaminant concentrations, document concentration changes related to common preparation methods and provide a basic risk-benefit analysis for select subsistence foods consumed by residents of Kotzebue, Alaska. STUDY DESIGN: Eleven organic nutrients and 156 persistent organic pollutants (POPs) were measured in foods derived from spotted seals and sheefish. METHODS: Nutrients in foodstuffs were compared to Daily Recommended Intake criteria. POPs were compared to Tolerable Daily Intake Limits (TDIL). RESULTS: Cooking, as well as absence/presence of skin during sheefish processing, altered nutrient and contaminant concentrations in seals and fish. Sheefish muscle and seal blubber were particularly rich in omega-3 fatty acids and seal liver in vitamin A. Seal liver exceeded the recommended upper limit for vitamin A. POP contribution to TDIL was >25% in all tissues except blubber, in which 4 POPS were present at >25% TDIL. No POPs exceeded TDIL in a serving of any tissue studied. The most prominent concerns identified were levels of vitamin A in spotted seal liver and certain POPs in blubber, warranting consideration when determining how much and how often these foods should be consumed. CONCLUSIONS: Preparation methods altering tissues from their raw state significantly affect nutrient and contaminant concentrations, thus direct evaluation of actual food items is highly recommended to determine risk-benefits ratios of traditional diets. Traditional foods provide essential nutrients with very limited risk from contaminants. We encourage the consumption of traditional foods and urge public health agencies to develop applicable models to assess overall food safety and quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".