Bibliographic record
Abstract
This is a report of the impact of the ice storm that struck eastern Canada on 04-09 January 1998. The storm deposited ice some 100 mm thick on the ground and on the electric power lines and eventually left 1.4 million households and much of the infrastructure without electrical power. Data were obtained through non-structured interviews of those involved. Most of the larger hospitals were equipped with emergency generating equipment and were able to provide most essential services. For most hospitals, non-emergency services were compromised. Many other medical facilities, including clinics had to be shut down, and smaller hospitals were forced to transfer some patients to larger institutions. In addition, hospitals experienced a marked increase in the number of emergency department visits including an increase in the number of persons with injuries, respiratory tract infections, or heart problems. A marked increase in carbon-monoxide intoxication was observed: 50 persons required the use of hyperbaric oxygen and six persons died of CO poisoning. Prehospital services not only experienced a marked increase in the number of emergency responses, but also were utilized to provide transportation of non-ill or injured persons, equipment, and supplies. Home care was interrupted and many patients dependent upon power had to be transported to hospitals. Many hospitals opened their buildings to provide shelter to the families of many of their employees and medical staff. This helped to keep staffing at a better level than if they had to find shelter and essential services elsewhere. The transmission and sharing of information was severely limited due in part to the loss of power and inability to access television. This led to the distribution of misleading or incorrect information. This storm was exemplary of our dependence upon electrical power and that we are not prepared to cope with the loss of electricity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".