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Record W2922453800 · doi:10.1097/oi9.0000000000000013

Trauma systems in North America

2019· article· en· W2922453800 on OpenAlexaffabout
Douglas W. Lundy, Edward J. Harvey, A. Alex Jahangir, Ross Leighton

Bibliographic record

VenueOTA International The Open Access Journal of Orthopaedic Trauma · 2019
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsDalhousie UniversityMcGill University
Fundersnot available
KeywordsTrauma centerTrauma careMedical emergencyMedicinePopulationQuality (philosophy)BusinessEnvironmental healthRetrospective cohort studySurgery

Abstract

fetched live from OpenAlex

North American trauma systems are well developed yet vary widely in form across the continent. Comparatively, the Canadian trauma system is more unified, and approximately 80% of Canadians live within 1 hour of a level I or II center. In the United States, trauma centers are specifically verified by the individual states and thus there tends to be more variability across the country. Although many states use the criteria developed by the American College of Surgeons Committee on Trauma, the individual agencies are free to utilize their own verification standards. Both Canada and the United States utilize efficient prehospital care, and both countries recognize that postdischarge care is a financial challenge to the system. Population dense areas offer rapid admission to well-developed trauma centers, but injured patients in remote areas may have challenges regarding access. Trauma centers are classified according to their capabilities from level I (highest ability) to level IV. Although each trauma system has opportunities for improvement, they both provide effective access and quality care to the vast majority of injured patients.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.059
GPT teacher head0.378
Teacher spread0.319 · 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.

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

Citations22
Published2019
Admission routes2
Has abstractyes

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