Canada's National Advisory Committee on Immunization (NACI): Evidence-based decision-making on vaccines and immunization
Bibliographic record
Abstract
The National Advisory Committee on Immunization (NACI) provides medical, scientific, and public health advice on the use of vaccines in Canada. This article describes the structure and processes of NACI, as well as its approach to evidence-based decision-making. In a rapidly evolving and complex immunization environment, NACI has faced challenges in its endeavour to make thorough and timely evidence-based recommendations. Making population-level recommendations without formally considering the full spectrum of public health science (e.g. cost-effectiveness) presents difficulties in the implementation of NACI's recommendations. Although an improved and more transparent evidence-based NACI decision-making process is now in place, this is continuing to evolve with a current review of structures and processes underway to further improve effectiveness and efficiencies.
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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 | 0.113 | 0.178 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.007 | 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".