Monitoring the Well-being of AusMAT Members Deployed to Fiji following Tropical Cyclone (TC) Winston
Bibliographic record
Abstract
Study/Objective: To study the lessons learned from the joint deployment. Background: On April 16 th 2016, at 6:58 pm. an earthquake of 7.8 Richter scale, hit west of Ecuador. As a result 673 people died, 4,859 injured, 8,000 displaced, 51 health care facilities damaged, and 593,000 persons had reduced access to health care services. The Canadian Red Cross together with the Ecuadorian Red Cross deployed (on April 20 th ) Emergency Medical units to support the affected population. The units were deployed in Jama and El Matal, and later moved to Pedernales, where they stayed until September 30 th when the services were taken over by the Ministry of Health (MoH). Methods: Data was collected from the unit's statistics, as well as from the operation's debriefing. Results: A total of 46,356 patients have been treated in the fixed facilities and the mobile clinic. There were 31,821 (68.6%) patients for internal medicine, 3,039 patients with GOB (mass or lump) needs (6.5 %), and Odontology needs became an issue with 3,137 (6.7 %). Conclusion: Successful joint deployment of an International and National team. Hand-over of the EMU from the Canadian RC to the Ecuadorian RC serves as crucial local capacity building for the ERC for future disasters. The Ecuadorian Red Cross High Technological Institute, the biggest training school for paramedics in the country, served as a major resource in the response (initial and long term) allowing the deployment of more than 2,000 persons to the affected areas. This earthquake has been the only large scale disaster the country has faced in 10 years. The response capacities have been increased significantly post disaster.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".