Bibliographic record
Abstract
The Chemical, Biological, Radiological, Nuclear and Explosives (CBRNE) Research and Technology Initiative (CRTI) is part of Canada's response, helping to sharpen the focus of our scientific and security communities on the areas that are the most relevant to today's realities. Many previous and ongoing CRTI projects have greatly strengthened Canada's preparedness for CBRNE events. However, there is a need to increase the preparedness for dealing with vulnerable population groups, such as children, elder citizens and persons with special medical needs. The Workshop on Emergency Preparedness for Vulnerable Population Groups was held on 2 and 3 March 2009 in Ottawa, Canada. Its purpose was to enhance communications within the emergency community response network, identify the needs and gaps of emergency preparedness against CBRNE events for vulnerable population groups and to eventually generate a plan for the development of emergency casualty management capabilities for these groups. This two-day workshop consisted of 16 presentations and 3 posters spanning a broad range of interests. The topics covered included presentations and discussions on: CRTI initiatives; mandates and priority areas for research; identification of threats to vulnerable populations and specific factors that influence vulnerabilities; identification of vulnerable or at-risk populations; addressing their special life stage and subpopulation vulnerabilities and needs; the requirements for special considerations for emergency management; lessons learned from previous emergencies, disasters and case studies; medical, physical and psychosocial consequence management strategies; and limitations including therapeutic product disposition. All discussions were targeted towards identifying the appropriate populations and their needs in order to improve emergency response outcomes. It is hoped that some of the recommendations coming from this workshop will provide guidance for new CRTI research priorities.
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.488 | 0.293 |
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".