Microbiota in the ptarmigan intestine - an Inuit delicacy and its potential in popular cuisine
Bibliographic record
Abstract
Abstract The consumption of prey intestines and their content, known as gastrophagy, is well-documented among Arctic Indigenous peoples, particularly Inuit. In Greenland, Inuit consume intestines from various animals, including the ptarmigan, a small herbivorous grouse bird. While gastrophagy provides the potential to transfer a large number of intestinal microorganisms from prey to predator, including to the human gut, its microbial implications remain to be investigated. This study addresses this gap by investigating the microbial composition of the Greenlandic rock ptarmigan’s gastrointestinal tract by analyzing the crop, stomach, and intestines while also comparing it with the microbiota found in garum, a fermented sauce made from ptarmigan meat and intestines. Through 16S rRNA gene sequencing, we assessed whether garum made from ptarmigan intestines provides access to microbial diversity otherwise only accessible through gastrophagy. Our findings reveal that garum made from ptarmigan intestines displayed distinct flavors and microbial composition similar to that found in the ptarmigan gut and intestines, highlighting the potential role of fermented products in mediating food microbial diversity associated with Indigenous food practices. Furthermore, our study underscores the broader importance of understanding microbial diversity in different food systems, particularly in the context of shifting dietary patterns and concerns about diminishing food microbial diversity. By elucidating the microbial richness gained through gastrophagy this research contributes to a deeper understanding of traditional and Indigenous foodways and their implications for human gut health.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".