Bibliographic record
Abstract
Antimicrobial resistance is a growing threat to the effective treatment of an ever-increasing range of infections caused by microorganisms, especially bacteria and fungi. The rise of resistance has clear implications for the choice of empirical therapy and may influence treatment outcomes. Detailed knowledge of the rates of antimicrobial resistance at both local and national levels is essential to inform such choices. Therefore, it is very welcome that in this JAC Supplement, data from the CANWARD study are presented. The CANWARD surveillance programme monitors rates of resistance in a range of bacterial and fungal pathogens causing infections in both inpatients and outpatients in Canada. In this Supplement, 10 years of longitudinal surveillance data (2007–16) are presented. Pathogens included are carbapenem-resistant and XDR Pseudomonas aeruginosa, ESBL-producing Escherichia coli and Klebsiella pneumoniae, Streptococcus pneumoniae, MRSA and Candida species. National surveillance data at this scale are both rare and invaluable when determining or contrasting antimicrobial resistance trends over time in specific geographic areas. In addition, the international nature of the antimicrobial resistance epidemiology means that these data should be of interest to public health and clinical researchers across the globe. Engeline van Duijkeren Russell Hope Nathan P. Wiederhold None to declare.
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 | 0.000 | 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".