Shifting Climates, Foods, and Diseases: The Human Microbiome through 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
Human evolution has been punctuated by climate anomalies, structuring environments, deadly infections, and altering landscapes. How well humans adapted to these new circumstances had direct effects on fitness and survival. Here, how the gut microbiome could have contributed to human evolutionary success through contributions to host nutritional buffering and infectious disease resistance is reviewed. How changes in human genetics, diet, disease exposure, and social environments almost certainly altered microbial community composition is also explored. Emerging research points to the microbiome as a key player in host responses to environmental change. Therefore, the reciprocal interactions between humans and their microbes are likely to have shaped human patterns of local adaptation throughout our shared evolutionary history. Recent alterations in human lifestyle, however, are altering human microbiomes in unprecedented ways. The consequences of interrupted host-microbe relationships for human adaptive potential in the future are unknown.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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