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
Bacteria communicate through the production of diffusible signal molecules termed autoinducers. The molecules are produced at basal levels and accumulate during growth. Once a critical concentration has been reached, autoinducers can activate or repress a number of target genes. Because the control of gene expression by autoinducers is cell-density-dependent, this phenomenon has been called quorum sensing. Quorum sensing controls virulence gene expression in numerous micro-organisms. In some cases, this phenomenon has proven relevant for bacterial virulence in vivo. In this article, we provide a few examples to illustrate how quorum sensing can act to control bacterial virulence in a multitude of ways. Several classes of autoinducers have been described to date and we present examples of how each of the major types of autoinducer can be involved in bacterial virulence. As quorum sensing controls virulence, it has been considered an attractive target for the development of new therapeutic strategies. We discuss some of the new strategies to combat bacterial virulence based on the inhibition of bacterial quorum sensing systems.
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 | 0.002 | 0.001 |
| 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