Canada has an opportunity to address antimicrobial resistance through COVID-19 recovery spending
Bibliographic record
Abstract
Antimicrobial Resistance (AMR) causes more than a million deaths globally per year due to infections incurable with currently available antibiotics. Failing to effectively address AMR will have significant negative consequences for Canadians and the Canadian economy. Canada is behind on allocation of required funding and nationally coordinated AMR mitigation strategies relative to other high-income countries. A Pan-Canadian AMR action plan and development of a new governance model is pending. Recent AMR-specific funding commitments are significant but fall short while distribution of funds indicate a siloed approach. Canada could initiate progress towards AMR mitigation through incorporation within the scope of budget allocations intended for COVID-19 recovery and mitigation efforts. We discuss the following components for inclusion: development of infectious disease diagnostics and therapeutics; antimicrobial stewardship interventions in long-term care and Indigenous communities; environmental monitoring of AMR; comprehensive antimicrobial use, and AMR surveillance; and support for capacity-building in low and middle-income countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".