Bibliographic record
Abstract
The Canadian Pandemic Influenza Preparedness: Planning Guidance for the Health Sector (CPIP) is a guidance document that outlines key health sector preparedness activities designed to ensure Canada is ready to respond to the next influenza pandemic.This article outlines Canada's pandemic influenza surveillance strategy as described in the CPIP Surveillance Annex.The strategy builds on the surveillance activities used for seasonal influenza and incorporates lessons learned from the 2009 H1N1 pandemic, including improved information sharing, improved electronic links among Federal/Provinical/Territorial (FPT) partners and improved surveillance for Indigenous communities.Key elements of the surveillance strategy include early detection and investigation of a novel influenza virus through the reporting of cases or clusters of severe acute respiratory infections and laboratory detections of novel influenza viruses.Community-based surveillance will provide information on clinical severity, age groups affected and risk factors associated with severe disease.Severe outcome surveillance will capture data on hospitalizations and deaths.Laboratory surveillance will include weekly reports of respiratory virus detections.The response activities are adaptable to the demands of different levels of pandemic activity and impact, supported by a set of triggers for the activation and deactivation.Surveillance will be linked with other response components, such as communications, research, assessment and evaluation.This is an evergreen document that will be updated regularly.
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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".