Community emergency department utilization following a natural disaster (the Goderich Tornado)
Bibliographic record
Abstract
INTRODUCTION: On 21 August 2011 an F3 tornado hit the Canadian town of Goderich, Ontario, leaving 40 people injured and one dead. Specific medium-term changes in utilization of health care following a disaster have not been analyzed in medical literature. Documenting the emergency department utilization through this subacute period would be helpful to enable institutions and healthcare practitioners to be better prepared for future events. METHODS: Alexandra Marine and General Hospital in Goderich. All emergency department visits made during the 30 days after the Tornado in 2011 (intervention group), 30 days prior to the tornado in 2011 (primary control group), and during the similar calendar period of 30 days after the tornado in 2010 (seasonal control group) were reviewed. Medical diagnoses of all patients who presented at the emergency department were collected and compared. RESULTS: <0.001). CONCLUSIONS: This study identifies the medical conditions that are most likely to be seen in an emergency department following a tornado in a rural Ontario community. This information serves to inform the medical community and other hospitals how to increase their level of preparedness should a comparable disaster occur again in the future.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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".