Concentrations of selected persistent organochlorine contaminants in store-bought foods from northern Alaska
Bibliographic record
Abstract
OBJECTIVES: We address marine and terrestrial mammal blubber, liver, muscle, kidney, heart, tongue, maktak and maktaaq (epidermis and blubber from bowhead, beluga whales, respectively), and fish muscle and livers, as commonly consumed tissues in subsistence communities across northern Alaska in the context of organochlorine (OC) contamination of store-bought foods. Human exposure to contaminants from biota, as part of a subsistence diet, has been superficially evaluated in numerous studies (focused on liver and blubber), but are limited in the type of tissues analyzed, and rarely consider the contaminants in the alternatives (i.e., store-bought foods). STUDY DESIGN: Concentrations from published literature on selected persistent organochlorine contaminants (OCs) in eight tissues of the bowhead whale and other biota (1) were compared to store-bought foods evaluated in this study. RESULTS: As expected, store-bought foods had lower concentrations of OCs than some tissues of the marine mammals (especially blubber, maktak, and maktaaq). However, blubber is rarely eaten alone and should not be used to give consumption advice unless considered as a portion of the food item (i.e., maktak). This study indicates that the store-bought food alternatives have detectable OC concentrations (e.g., < 0.01 to 22.5 ng/g w.w. for hexachlorobenzene) and, in many cases, have greater OC concentrations than some subsistence food items. Many wildlife tissues had OC concentrations similar to those quantified in local store-bought food. CONCLUSIONS: Switching from the traditional diet to western store-bought foods will not always reduce exposure to OCs. However, raw blubber-based products are clearly more contaminated with OCs due to lipid content. A detailed profile of traditional/country foods and western foods consumed by subsistence communities of northern Alaska is required to address chronic exposure in more detail for the diverse sources of foods (subsistence use and commercially available) and the widely varying concentrations of contaminants reported therein. This should be combined with biomonitoring people dependent upon subsistence foods. Further assessment of essential and non-essential elements, emerging contaminants (e.g. brominated flame retardants), etc. should be conducted in order to improve our understanding of the differences and similarities between wildlife and store-bought foods.
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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 | 0.001 |
| 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) | 0.001 | 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".