Bibliographic record
Abstract
Clostridium difficile is an emerging pathogen that causes C difficile-associated diarrhea, an important nosocomial infection. Control of this infection remains a challenge, and much needs to be determined about the antimicrobial resistance of the organism, antibiotic stewardship, contamination of the patient environment, and various host factors that determine susceptibility or resistance to infection. A national symposium focusing on C difficile infections, the Clostridium difficile Symposium on Emerging Issues and Research, was hosted on November 23, 2004, by the Department of Medical Microbiology and Infectious Diseases at the University of Manitoba, Winnipeg, Manitoba, in partnership with the Canadian Institutes of Health Research. This symposium, which aimed to summarize key research issues regarding C difficile infections in Canada, had the following objectives: to provide a forum for learning and discussion about C difficile and its impact on the health of Canadians; to identify the key research issues that should be addressed; and to explore potential research funding opportunities and collaboration. The present report summarizes key research issues identified for C difficile infections in Canada by addressing four major themes: diagnosis and surveillance, infection prevention and control, antibiotic stewardship, and clinical management.
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 | 0.037 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".