Looking for Solutions to the Pitfalls of Developing Novel Antibacterials in an Economically Challenging System
Bibliographic record
Abstract
The increase in antibacterial resistance (ABR) currently equates in the minds of many with the distant fear that certain antibiotics will not work in 30 years on certain bacteria found in places the majority of us never go to. However, in reality, rising ABR already seriously threatens the effectiveness of compounds with which we treat common bacterial infections, which means that ABR is currently and will continue to undermine the foundations of modern medicine, including surgery and cancer treatment in hospitals, cities and countries across the world. That is why ABR is widely considered a global threat and one of the biggest problems of our current civilization. Conversely, antibiotic developments to market are few. Therefore, in this paper, we have illustrated the barriers to antimicrobial R&D the following questions and provided solutions to effective antimicrobial R&D.
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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 | 0.002 | 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".