Dietary practices in isolated First Nations communities of northern Canada: combined isotopic and lipid markers provide a good qualitative assessment of store-bought vs locally harvested foods consumption
Bibliographic record
Abstract
OBJECTIVE: In First Nations communities of northwestern Ontario, where rates of type 2 diabetes mellitus are some of the highest in the world, ascertaining wild food dietary practices is extremely challenging owing to seasonal availability, environmental factors, life circumstances and language/cultural barriers. The purpose of this study was to determine whether analysis of isotopic and fatty acid (FA) profiles could provide more comprehensive information to discriminate between three categories of wild food consumption (that is, plants and animals) in two isolated First Nations communities of northwestern Ontario. In addition, this analysis also highlights whether wild food consumption as practiced in these two communities can increase circulating levels of polyunsaturated FAs (PUFAs), which provide a number of important metabolic benefits that could impact the prevention/treatment of T2DM. RESULTS: (13)C enrichment (in expired CO2, plasma and hair), (15)N enrichment (in hair) and FA profiles in plasma phospholipids (phospholipid fatty acid (PL-FA)) were quantified in men and in women consuming various amounts of wild food. (13)C/(12)C ratios were lower and (15)N/(14)N ratios were higher in participants consuming wild food at least once a week. In addition, FA results indicated that the relative contributions of 20:4 Ω-6 and 22:6 Ω-3 to total PL-FAs were higher and 18:2 Ω-6 lower in wild food consumers. CONCLUSION: Together, these findings confirm that isotopic and lipid markers discriminate between the different wild food categories in these two First Nations communities. Knowing the close relationship between dietary intake and the potential role of PUFA in the prevention/treatment of obesity and obesity-related diseases, it is critical to accurately measure the composition of diet for individuals in their specific environments.
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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 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".