Evolution of Drug Resistance in <i>Candida Albicans</i>
Bibliographic record
Abstract
The widespread deployment of antimicrobial agents in medicine and agriculture is nearly always followed by the evolution of resistance to these agents in the pathogen. With the limited availability of antifungal drugs and the increasing incidence of opportunistic fungal infections, the emergence of drug resistance in fungal pathogens poses a serious public health concern. Antifungal drug resistance has been studied most extensively with the yeast Candida albicans owing to its importance as an opportunistic pathogen and its experimental tractability relative to other medically important fungal pathogens. The emergence of antifungal drug resistance is an evolutionary process that proceeds on temporal, spatial, and genomic scales. This process can be observed through epidemiological studies of patients and through population-genetic studies of pathogen populations. Population-genetic studies rely on sampling of the pathogen in patient populations, serial isolations of the pathogen from individual patients, or experimental evolution of the pathogen in nutrient media or in animal models. Predicting the evolution of drug resistance is fundamental to prolonging the efficacy of existing drugs and to strategically developing and deploying novel drugs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".