Better understanding of food and human microbiomes through collaborative research on Inuit fermented foods
Bibliographic record
Abstract
Reports on fermented, animal-sourced foods made by Inuit around the circumpolar North have lacked consideration for their unique microbiota and the geo-socio-cultural contexts in which they are made, often resulting in reinforced negative stereotypes. Deficit-based approaches to studying Inuit fermented foods overlook the fact that they have long been considered healthy and integral to Inuit diets. Inuit have deep knowledge on the harvesting, preparation, sharing, and consumption of fermented foods that research efforts must learn from and acknowledge. Our preliminary research into Inuit animal-sourced fermented foods expands current knowledge about the microorganisms needed to make them, and points to a potential to understand how these and other fermented foods impact the human gut microbiome. We provide recommendations for microbiological research on Inuit fermented foods that centers Inuit knowledge within the specific geographic, social, and cultural contexts in which these foods are made.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".