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Record W2166374686 · doi:10.1017/s1049023x00025589

The Ice Storm in Eastern Canada 1998 KAMEDO-Report No. 74

2001· article· en· W2166374686 on OpenAlexaboutno aff
Louis Riddex, Uno Dellgar

Bibliographic record

VenuePrehospital and Disaster Medicine · 2001
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStaffingMedical emergencyMedicineEmergency medical servicesEmergency medicineStormNursingGeographyMeteorology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.297
Threshold uncertainty score0.804

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.013
GPT teacher head0.253
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2001
Admission routes1
Has abstractyes

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