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Record W4292159269 · doi:10.12927/cjnl.2022.26869

Leading Canadian Nurses into the Genomic Era of Healthcare

2022· article· en· W4292159269 on OpenAlexaffvenueabout
Jacqueline Limoges, April Pike, Sarah Dewell, Ann Meyer, Rebecca Puddester, Lindsay Carlsson

Bibliographic record

VenueNursing leadership · 2022
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsPrincess Margaret Cancer CentreOntario GenomicsUniversity of Northern British ColumbiaAthabasca UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsHealth careGenomicsNursingNursing practiceLiteracyMedical educationPsychologyMedicinePolitical sciencePedagogyGenetics

Abstract

fetched live from OpenAlex

Genomics is having a profound impact on every aspect of healthcare. To support nurses to develop genomic literacy and integrate genomics into care, an engagement framework was created. The framework uses principles of nursing intraprofessional collaboration, the knowledge-to-action cycle and the diffusion of innovations theory. This framework was used to identify six key priorities for action and leadership strategies to accelerate and sustain the nurses' engagement with genomics. With leadership and genomic literacy, nurses can fully participate in the creation and implementation of new care pathways, deliver education, advance research linked to genomics and improve patient experience and health outcomes.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.792
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.388
GPT teacher head0.439
Teacher spread0.051 · 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 designOther design
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

Citations13
Published2022
Admission routes3
Has abstractyes

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