Cell-density-dependent regulation of streptococcal competence
Bibliographic record
Abstract
INTRODUCTION A brief history In the 1920s Frederick Griffith, a medical officer at the Ministry of Health in Britain, made a significant discovery regarding Streptococcus pneumoniae , a bacterium that caused a pneumonia epidemic in London. While examining the strain variability within different groups of pneumococci, Griffith noted that an avirulent strain of the bacterium could revert to the virulent type or remain unchanged following subculture (37). Because this phenomenon enabled the bacterium to acquire a novel heritable phenotype, Griffith coined the term “transformation principle” to describe the phenotypic changes he observed. In his classic experiment, Griffith studied a highly infective, encapsulated S strain that formed smooth colonies, and an avirulent R strain, which had no capsule and formed rough colonies when grown on blood agar (37). When healthy mice were injected with the S strain, they died of septice- mia, whereas separate admission of the R strain or the heat-killed S strain appeared to be harmless. However, when the live R strain and the heat-killed S strain were injected simultaneously, the mice died. Surprisingly, when blood samples drawn from these dead animals were analyzed, both R and S live strains were detected. Based on these results, Griffith concluded that a “transforming factor”, present in the heat-killed S strain, was able to “transform” an avirulent R strain into a capsulated, virulent S strain. Over the next few decades, Griffith's inspiring work on transformation was followed up by a number of scientists.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".