Gut Microbial Intersections with Human Ecology and Evolution
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although microbiome science is relatively young, our knowledge of human-microbiome interactions is growing rapidly and has already begun to transform our understanding of human ecology and evolution. Here we summarize our current understanding of three-way interactions between the gut microbiota, human ecology, and human evolution. We review the factors driving microbiome variation within and between individuals and populations, as well as comparative data from nonhuman primates that allow a more direct examination of microbial relationships with host ecology and evolution. Collectively, these data sets can help illuminate generalizable principles governing host-microbiome-environment interactions, the processes contributing to bidirectional influences between the human gut microbiota and the human ecological niche, and past changes in the human microbiome that may have harbored consequences for human adaptation. Developing richer insight into host-microbiome-environment interactions will ultimately broaden our view of human biology and its response to changing environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it