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Record W2003255502 · doi:10.7748/ns.29.1.44.e8730

Phantom limb pain: a nursing perspective

2014· article· en· W2003255502 on OpenAlex
Anila Virani, Theresa Green, Tanvir Chowdhury Turin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNursing Standard · 2014
Typearticle
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPhantom limbAmputationPhantom limb painPsychological interventionNeuropathic painPerspective (graphical)DistressPhenomenonMedicineNursingProcess (computing)Physical medicine and rehabilitationQuality of life (healthcare)PsychologyPhysical therapyIntensive care medicineComputer sciencePsychiatryClinical psychologyAnesthesia

Abstract

fetched live from OpenAlex

Phantom limb pain (PLP) is a neuropathic pain condition occurring after amputation of a limb. PLP affects amputees' quality of life and results in loss of productivity and psychological distress. The origin of pain from a non-existing limb creates a challenging situation for both patients and nurses. It is imperative to provide patients and nurses with the knowledge that PLP is a real phenomenon that requires care and treatment. This knowledge will lead to reduced problems for patients by allowing them to talk about PLP and ask for help when needed. Understanding of this phenomenon will enable nurses to appreciate the unique features of this form of neuropathic pain and apply appropriate techniques to promote effective pain management. Performing accurate and frequent assessments to understand the unique characteristics of PLP, displaying a non-judgemental attitude towards patients and teaching throughout the peri-operative process are significant nursing interventions.

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.

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)0.000
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 score0.927
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.322
Teacher spread0.308 · 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