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Record W2159603062 · doi:10.1177/1074840708328123

Excellence in Nursing

2008· review· en· W2159603062 on OpenAlexaboutno aff
Erla Kolbrun Svavardottir

Bibliographic record

VenueJournal of Family Nursing · 2008
Typereview
Languageen
FieldHealth Professions
TopicFamily and Patient Care in Intensive Care Units
Canadian institutionsnot available
Fundersnot available
KeywordsOperationalizationExcellenceNursingIntervention (counseling)MedicineNurse educationDoctor of Nursing PracticePsychologyMedical education

Abstract

fetched live from OpenAlex

An innovative opportunity is being created by nursing leaders from practice and education in Iceland to implement Family Systems Nursing at an institutional level on all units and divisions with the Landspitali University Hospital. This article describes the phases of the implementation model for knowledge translation that will be operationalized over four years. The goals of implementing Family Systems Nursing at the Landspitali University Hospital are to (a) educate all practicing nurses in Family Systems Nursing and, in particular, the Calgary family assessment and intervention models; (b) strengthen practicing nurses' clinical skills for intervening with families by offering specific clinical training courses to all nurses using family skills labs; and (c) explore and assess the difference that the theoretical and clinical programs make for the nurses, the patients and their families, and the nurses' practice (the family-nurse relationship).

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)0.006
metaresearch head score (Gemma)0.010
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0020.004
Scholarly communication0.0060.004
Open science0.0020.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0160.007

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 head0.283
GPT teacher head0.529
Teacher spread0.246 · 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
GenreReview

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

Citations37
Published2008
Admission routes1
Has abstractyes

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