Characterization of Antibiotic Compounds By Electrochemistry
Bibliographic record
Abstract
The rise of antibiotic resistance has become a severe problem around the world. According to a report from the Centers for Disease Control and Prevention, approximately two million illnesses and 23,000 deaths are caused by antibiotic resistance each year in the United States alone and 10 million deaths worldwide each year. The Public Health Agency of Canada reported antimicrobial resistant is expected to kill nearly 400,000 Canadians and cost $400 billion in GDP by 2050. Electrochemistry with its high sensitivity has caught significant attention in the fields of biosensing and medical diagnostics over the last decade. This presentation describes our efforts to detect and quantify drug efflux from living bacteria. To this end, cyclic voltammetry and chronoamperometry were employed to characterize common antibiotics as well as newly investigational compounds, such as the antibiotic hybrid ciprofloxacin-tobramycin. Understanding the diffusional processes and electrochemical behavior of these drugs, first steps have been taken towards their quantitative detection in drug-sensitive and drug-resistant Pseudomonas bacteria.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".