Determining the Rate of Development of Antibiotic Resistance to Streptomycin and Doxycycline in Escherichia coli
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
Antibiotic resistance is a pressing issue in the medical field today. It is important to understand the development of bacterial resistance to implement effective preventative measures against antibiotic resistant bacteria. This study investigated the rate at which Escherichia coli (E. coli), a common pathogen, developed resistance to streptomycin and doxycycline, as Oz et al. (2014) showed differing levels of resistance in E. coli to these two antibiotics. The development of antibiotic resistance was measured by adding E. coli to 96-well plates in the presence of increasing doses of doxycycline, streptomycin, or a combination treatment. Successive generations were added to the same treatments to see whether they would grow at higher concentrations of antibiotic. The change in minimum inhibitory concentration for streptomycin and doxycycline was determined as the bacteria became increasingly resistant to each antibiotic. The fastest rate of antibiotic resistance was observed for streptomycin, with doxycycline resistance exhibiting a slower rate of development. The rate of resistance development for the combination treatment was the slowest, potentially due to small differences in target domains. Some cross-resistance was also observed. This study provides a small-scale methodological basis and preliminary insight on antibiotic resistance trends for two antibiotic classes and a combination treatment.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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