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Record W2020333817 · doi:10.1136/jnnp.2006.091884

Nova Scotia Improving the delivery of stroke care services

2006· article· en· W2020333817 on OpenAlexaboutno aff
Gord Gubitz

Bibliographic record

VenuePractical Neurology · 2006
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsnot available
Fundersnot available
KeywordsNova scotiaIrishStroke (engine)Ethnic groupPopulationMedicineAcute strokeFamily medicinePolitical scienceHistoryNursingEthnologyEnvironmental healthEmergency departmentEngineering

Abstract

fetched live from OpenAlex

It has been more than a decade since the initial publication of Langhorne and his colleagues’ systematic review1 which demonstrated that organised stroke care is superior to other systems of care for patients with stroke. Since then, this message has been repeated, advertised, and written about extensively, and has formed the basis of many national stroke care guidelines and consensus statements around the world. Unfortunately, in many (some would say most) places, the actual organisation of acute stroke care services has not yet been formalised, and the relatively simple messages of the systematic review have not been adopted in a consistent manner, to the detriment of countless people with stroke and their families. Fortunately, this is beginning to change—a change that is beginning to happen in Nova Scotia, and throughout Canada. Nova Scotia is one of Canada’s Maritime provinces, and is home to just under one million people. Many of the population are descendents of the British, Irish, and French, but the province is becoming increasingly multi-ethnic. Approximately 60% of the population live outside major cities. As a …

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.081
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.002

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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2006
Admission routes1
Has abstractyes

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