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Record W1869755258 · doi:10.5430/jnep.v5n11p81

Specialized stroke nursing program using an inter-professional approach: A nurse-driven education initiative of one stroke hospital in Saudi Arabia

2015· article· en· W1869755258 on OpenAlexvenueno aff
Elmer Catangui

Bibliographic record

VenueJournal of Nursing Education and Practice · 2015
Typearticle
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)NursingMedicineDependency (UML)PopulationUnit (ring theory)Professional developmentMedical educationPsychologyEnvironmental health

Abstract

fetched live from OpenAlex

The incidence of stroke is remarkably increasing in the Kingdom of Saudi Arabia. The integration of evidence–based practice is essential in provision of specialist stroke care to all stroke patients. The King Abdullaziz Medical City (KAMC) in Riyadh has reconfigured the stroke services by creating a novel stroke model where all suspected stroke patients are directly admitted to the high dependency stroke unit (HDSU) in order to provide an integrated and specialized care to the stroke population. Prior to the launch of the new stroke model, training was imperative for all nurses. The article will describe the development and evaluation of the specialized stroke nursing programme using an inter-professional learning approach.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.188
GPT teacher head0.537
Teacher spread0.349 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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