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Record W4256618402 · doi:10.24124/2014/bpgub1633

Need for helicopter emergency medical services (HEMS) in rural British Columbia

2014· dissertation· en· W4256618402 on OpenAlexaffabout
Roberta Squire

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsWorkers Compensation Board of British ColumbiaUniversity of Northern British Columbia
Fundersnot available
KeywordsEmergency medical servicesMedical emergencyService (business)Emergency medical careMedicineGeographyEngineeringBusiness

Abstract

fetched live from OpenAlex

Currently, there is no dedicated helicopter emergency medical service (HEMS) in Northern British Columbia (BC). Injuries to workers in BC result in the loss of more economically productive years than heart disease and cancer combined and cost nearly $2.8 billion per year. Nearly three quarters of all people who die of trauma-related conditions in Northern BC do so before they can be brought to a hospital 82% in Northwestern BC, compared to 12% in Metro Vancouver (Cameron 2007 McKenna 2013). Minimizing the time from injury to optimal trauma care through the utilization of HEMS has been adopted as an essential component of emergency care infrastructures Globally. The purpose of this paper is to examine the opportunities, challenges and needs of a dedicated helicopter emergency medical system to service the remote regions of Northern BC. --Leaf iii.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.056
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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.

Opus teacher head0.008
GPT teacher head0.290
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2014
Admission routes2
Has abstractyes

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