Antimicrobial resistance programs in canada 1995-2010: a critical evaluation
Bibliographic record
Abstract
BACKGROUND: In Canada, systematic efforts for controlling antibiotic resistance began in 1997 following a national Consensus Conference. The Canadian strategy produced 27 recommendations, one of which was the formation of the Canadian Committee on Antibiotic Resistance (CCAR). In addition several other organizations began working on a national or provincial basis over the ensuing years on one or more of the 3 identified core areas of the strategy. Critical evaluation of the major programs within Canada which focused on antimicrobial resistance and the identified core components has not been previously conducted. FINDINGS: Data was collected from multiple sources to determine the components of four major AMR programs that were considered national based on their scope or in the delivery of their mandates. Assessment of program components was adapted from the report from the International Forum on Antibiotic Resistance colloquium. Most of the programs used similar tools but only the Do Bugs Need Drugs Program (DBND) had components directed towards day cares and schools. Surveillance programs for antimicrobial resistant pathogens have limitations and/or significant sources of bias. Overall, there has been a 25.3% decrease in oral antimicrobial prescriptions in Canada since 1995, mainly due to decreases in β lactams, sulphonamides and tetracyclines in temporal association with multiple programs with the most comprehensive and sustained national programs being CCAR and DBND. CONCLUSIONS: Although there has been a substantial decrease in oral antimicrobial prescriptions in Canada since 1995, there remains a lack of leadership and co-ordination of antimicrobial resistance activities.
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 | 0.047 | 0.089 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.023 | 0.026 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 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 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".