How the Physical Environment Shapes the Microbiota
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
Living systems, from micro- to macro-scales, are strongly impacted by physical factors such as temperature, pH, and the concentration of compounds in their surrounding environment. In the macro-world, it is obvious that small changes in these parameters can have profound, and even devastating, impacts on an ecosystem. For example, in the case of global warming, a change in climate, and specifically a few degrees in temperature, has taken one million species of animals to the brink of extinction. Scale things down 6 orders of magnitude, our gut microbiota also experiences similar changes in temperature due to disease. In this highly competitive environment, physical perturbations inflict long-term consequences on the microbiota ecosystem and, in turn, on the host organism. My laboratory is exploring the feedback between the gut's physical environment, the microbiota, and disease. Our research highlights the importance of measuring physical parameters for the prediction of microbial dynamics and microbiota therapies.
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 | 0.000 |
| 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