Bibliographic record
Abstract
The world of gastrointestinal (GI) bacteria is one of the most complex and intricate of the microbial domain. These bacteria are confronted with a constantly changing (and often hostile) environment, including fluctuations in both physical and chemical conditions. Neighboring microorganisms not only contend for substrate but even launch complex chemical attacks with the apparent purpose of disrupting the activity of their competitors. Yet, some species not only survive, they even flourish, in the GI tract because they possess the ability to adapt to these environmental fluctuations and assaults from other microbes. Such adaptation involves sophisticated programs in the bacterial cell that enable it to monitor its environment and make necessary adjustments of physiological activity and gene expression. Among these adjustments is the ability of cell-to-cell communication, biofilm formation, regulation of cytoplasmic pH, and maintenance of genetic diversity through mutation and horizontal gene transfer. As a consequence, bacteria in the GI tract often manifest very different physiological features than are observed for the same bacteria during routine laboratory cultivation. Key words: Gastrointestinal bacteria, bacteria, gastrointestinal tract, ruminal bacteria, biofilms, quorum-sensing, colonic bacteria
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.
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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".