Tactical EMS Deployment at the G7 Summit in Charlevoix, Quebec
Bibliographic record
Abstract
INTRODUCTIONThe G7 Summit was held in Charlevoix, Quebec (Canada) on June 8 and 9, 2018. The Urgences-santu00e9 Corporation (USC), in charge of pre-hospital emergency services in Montreal and Laval, was asked to intervene outside of its usual territory during the Summit, mainly because it has the only tactical medical team in the province of Quebec to be equipped and trained for high-risk situations.GOALPart of USCu2019s tactical medical team was deployed to the Charlevoix region from May 29 to June 10, 2018. The team had two responsibilities: act in the event of a chemical, biological, radiological, nuclear or explosive (CBRNE) attack and, in the event of social disturbance or violence, provide care for protestors and the police officers tasked with maintaining and restoring order.METHODThe mission required rigorous preparation to ensure the teamu2019s safety outside its usual area of activity, while maintaining full coverage of metropolitan Montreal, where the impacts of the G7 Summit were also felt. Emphasis was placed on intensive coaching of the tactical medics, on joint training, and on the coordination of intervention protocols across EMS, fire and law enforcement.RESULTSA total of 14 tactical medics and two managers were sent to Charlevoix for the Summit. Before their departure, three joint training days were held and our training center provided six days of training to our partners. DISCUSSION While no CBRNE incident or major social disorder occurred during the Summit, USC was able to gain more visibility and therefore reach out to different organizations on site. Close ties were developed with the Su00fbretu00e9 du Quu00e9bec (provincial police), with whom USC now regularly collaborates during training and interventions. The lessons learned also helped consolidate our extra-territorial deployment procedures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 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".