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Record W2558540815 · doi:10.1097/psn.0000000000000160

Using the Nursing Process to Identify and Treat Angioedema: A Case Study

2016· review· en· W2558540815 on OpenAlexaff
Tracey A. Hotta

Bibliographic record

VenuePlastic Surgical Nursing · 2016
Typereview
Languageen
FieldMedicine
TopicCoagulation, Bradykinin, Polyphosphates, and Angioedema
Canadian institutionsThornhill Medical (Canada)
Fundersnot available
KeywordsLoginLogo (programming language)World Wide WebComputer scienceInternet privacyProcess (computing)Register (sociolinguistics)Personally identifiable informationComputer security

Abstract

fetched live from OpenAlex

The nursing process is the essential core of practice for registered nurses, independent of what field of nursing you have chosen. You learn it in nursing school and use it until you are no longer practicing. It is designed to train nurses how to develop a nursing care plan through critical thinking. Over the years it becomes a routine way of problem solving, but it is sometimes good to go back to the basics to remember the ground work. The focus of this article is to review the steps of the nursing process when faced with a complication, using our critical thinking skills.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.125
GPT teacher head0.473
Teacher spread0.348 · 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 designCase report
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

Citations4
Published2016
Admission routes1
Has abstractyes

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