MétaCan
Menu
Back to cohort

What Nurses Want

2008· article· en· W2323390070 on OpenAlexaff
Tammie Di Pietro, Geraldine Coburn, Narissa Dharamshi, Diane Doran, John Mylopoulos, André Kushniruk, Lynn Nagle, Souraya Sidani, Ann E. Tourangeau, Brenda Laurie‐Shaw, Nancy Lefebre, Cheryl Reid‐Haughian, Greg McArthur

Bibliographic record

VenueJournal of Nursing Care Quality · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsUsabilitySoftware portabilityPoint of careQuality (philosophy)Point (geometry)NursingComputer scienceMedicineHuman–computer interaction

Abstract

fetched live from OpenAlex

We investigated the usability of personal digital assistants (PDAs) to improve research utilization and timely access to electronic practice information to assist in clinical decisions. Nurses used a decision support tool on a PDA to collect point-of-care outcomes data. Follow-up interviews documented usability. Nurses liked the portability and size of the PDA, as well as ease of use of the PDA software. Electronic decision support tools at point of care have the potential to improve nurses' research utilization and quality of care.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.484
GPT teacher head0.651
Teacher spread0.167 · 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 designQualitative
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

Citations21
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nursing Care QualitySame topicHealth Sciences Research and EducationFrench-language works237,207