Sustainable solutions to the continuous threat of antimicrobial resistance
Bibliographic record
Abstract
To combat antimicrobial resistance (AMR), advocates have called for passage of the Pioneering Antimicrobial Subscriptions To End Upsurging Resistance (PASTEUR) Act in the United States, which would appropriate $6 billion in new taxpayer-funded subsidies for antibiotic development. However, the number of antibiotics in clinical development, and US Food and Drug Administration approvals of new antibiotics, have already markedly increased in the last 15 years. Thus, instead of focusing on more economic subsidies, we recommend reducing selective pressure driving AMR by (1) establishing pay-for-performance mechanisms that disincentivize overprescribing of antibiotics, (2) focusing existing research and development funding on strategies that decrease reliance on antibiotics, and (3) changing regulation or law to require specialized training in antibiotic stewardship for a clinician to be able to prescribe new antibiotics that target unmet AMR need. To stabilize the antibiotic market, we recommend (1) establishment of an advisory board of clinical practitioners to more accurately target existing antibiotic incentives and (2) endowment of nonprofit companies that sustainably self-fund antibiotic discovery, creating a bench of molecules that can be partnered with industry at later stages of development.
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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 | 0.001 | 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 | 0.001 | 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".