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Record W2746648482 · doi:10.1097/ans.0000000000000180

Characteristics of Reviews Published in Nursing Literature

2017· review· en· W2746648482 on OpenAlexaff
Coleen E. Toronto, Brenna L. Quinn, Ruth Remington

Bibliographic record

VenueAdvances in Nursing Science · 2017
Typereview
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsToronto Public Health
Fundersnot available
KeywordsSystematic reviewData extractionCritical appraisalRigourMEDLINEPsychologyNursing literatureProcess (computing)Quality (philosophy)Management scienceMedicineComputer scienceAlternative medicinePolitical scienceEpistemologyEngineering

Abstract

fetched live from OpenAlex

Integrative and systematic reviews present synthesized research. Scholars have called for increased rigor and reporting in reviews. The purpose of this methodological review was to describe the characteristics of nurse-led reviews. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines directed the review process. Many reviews did not clearly report the search strategy used and methods for data extraction and quality appraisal, indicating that there has not been an increase in rigor. Authors of reviews are encouraged to report sufficient methodological details, so peer reviewers and consumers can determine whether the methods were rigorous enough to contribute meaningful results.

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)0.063
metaresearch head score (Gemma)0.441
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.940
Threshold uncertainty score0.333

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0630.441
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0600.088
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.003

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 head0.580
GPT teacher head0.620
Teacher spread0.040 · 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.

Study designObservational
DomainEvaluation
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

Citations8
Published2017
Admission routes1
Has abstractyes

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