Control of antimicrobial resistance in Canada: any lessons to learn?
Bibliographic record
Abstract
BACKGROUND: Over the past 15 years, repeated national meetings have developed recommendations for a Canadian antimicrobial resistance strategy. Despite this, in 2011 there is no comprehensive, integrated national program with appropriate governance and funding to address antimicrobial resistance. FINDINGS: The Public Health Agency of Canada supports a reference laboratory for diagnosis and characterization of selected resistant strains, targeted surveillance programs which monitor resistance trends for selected animal and human organisms, development of national infection control guidelines including for antimicrobial resistant organisms, and a few local pilot projects to address community acquired MRSA. Sporadic programs of variable intensity and quality are supported by some provinces, health regions and individual facilities but these are not comprehensive, standardized or integrated. Individual researchers and research groups, however, have published substantial information describing the prevalence and impact of resistance in Canada. CONCLUSIONS: Current review of activities by the Public Health Agency of Canada and initiatives by the National Coordinating Centre for Infectious Diseases may move the country forward in developing an effective national approach to address antimicrobial resistance.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".