Real-Time Impact Analysis and Response using a New Disaster Metrics: 2018 Sulawesi (Indonesia) Earthquake and Tsunami
Bibliographic record
Abstract
INTRODUCTION: The Richter Scale measures the magnitude of the seismic activity for an earthquake; however, it does not quantify the humanitarian need at the point of impact. This poses a challenge for humanitarian stakeholders in decision and policy making, especially in risk reduction, response, recovery, and reconstruction. The new disaster metrics tool titled "The YEW Disaster Severity Index" (DSI) was developed and presented at the 2017 World Congress of Disaster and Emergency Medicine, May 2017, Toronto, Canada. It uses a median score of three for vulnerability and exposure indicators, a median score percentage of 100%, and medium YEW DSI scoring of four to five as baseline, indicating the ability to cope within local capacity. Therefore, scoring more than baseline coping capacity indicates that external assistance is needed. This special real-time report was presented at the 2nd National Pre-Hospital Care Conference and Championship, October 2018, Malaysia. REPORT: The aim of this analysis is to present the real-time humanitarian impact and response to the 2018 earthquake and tsunami at Donggala and Palu, Sulawesi in Indonesia using the new disaster metrics YEW DSI. Based on the earthquake (measuring 7.7 on the Richter Scale) and tsunami at Donggala, the humanitarian impact calculated on September 29, 2018 scored 7.4 High in the YEW DSI with 11 of the total 17 indicators scoring more than the baseline coping capacity. The same YEW DSI score of 7.4 was scored on the earthquake and tsunami at Palu, with 13 of the total 17 indicators scoring more than baseline ability to cope within local capacity. Impact analysis reports were sent to relevant authorities on September 30, 2018. DISCUSSION & CONCLUSION: A State of Emergency was declared for a national response, which indicated an inability to cope within the local capacity, shown by the YEW DSI. The strong correlation between the earthquake magnitude, intensities, and the humanitarian impact at Donggala and Palu reported could be added into the science of knowledge in prehospital care and disaster medicine research and practice. As a conclusion, the real-time disaster response was found to be almost an exact fit with the YEW DSI indicators, demonstrating the inability to cope within the local capacity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".