Potential associations between environmental conditions and the gut microbiome of the Hadza hunter-gatherers
Bibliographic record
Abstract
The gut microbiome has co-evolved with humans over time, adapting according to environmental changes imposed by the host. Rural communities, such as the Hadza hunter-gatherers of Tanzania are exposed to unique environmental conditions that differ from those of urban communities. Many of these environmental factors are thought to impact gut microbial composition, which has led to an increased interest surrounding the analysis of the gut microbiome of these individuals. Here, we aimed to uncover the impact of water sources, geographical locations, and wildlife exposure on the gut microbiome of the Hadza people. Following parsing of amplicon sequencing data, analysis of the Hadza gut microbiota did not reveal any strong associations with individual water sources nor bush camp locations. However, similarities between the gut microbiome of the Hadza and of vervet monkeys were identified. These results highlight the complexity of the interplay between environmental factors unique to rural communities and the human gut microbiome. Our analysis of the Hadza gut microbiome adds to the body of knowledge that aims to provide insight into features representative of the ancestral human gut microbiome composition.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".