The National Advisory Committee on Infection Prevention and Control (NAC-IPC)
Bibliographic record
Abstract
This paper describes the work of the National Advisory Committee on Infection Prevention and Control (NAC-IPC), previously Infection Prevention and Control Expert Working Group, a longstanding external advisory body that provides subject matter expertise and advice to the Public Health Agency of Canada (PHAC) on the prevention and control of infectious diseases in Canadian health care settings. Originally established by Health Canada as the Infection Control Guidelines Steering Committee in 1992, this advisory board has been providing expert advice on infection prevention and control (IPC) guideline development for over 25 years. The NAC-IPC provides advice to inform the development of comprehensive or concise guidelines, quick reference guides and interim guidelines (usually for emerging pathogens), working closely with PHAC's national Healthcare-Associated Infections (HAIs) surveillance programs for Canadian health care facilities. PHAC's HAI-IPC professionals conduct the necessary literature research, data extraction, evidence synthesis, evidence grading (where applicable) and scientific writing for the guidelines. Due to the paucity of clinical trials and high quality observational studies to inform recommendations for emerging pathogens, expert opinion is critical for interpreting available evidence. .
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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 | 0.106 | 0.245 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.013 | 0.004 |
| Open science | 0.009 | 0.005 |
| Research integrity | 0.015 | 0.020 |
| Insufficient payload (model declined to judge) | 0.034 | 0.020 |
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".