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Record W3192213941 · doi:10.1136/ebnurs-2021-103443

Efficacy of non-pharmacological treatments of fatigue in individuals with end-stage disease

2021· letter· en· W3192213941 on OpenAlexaff
Terri Kean

Bibliographic record

VenueEvidence-Based Nursing · 2021
Typeletter
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsDiseaseMedicineStage (stratigraphy)Internal medicinePharmacologyBiology

Abstract

fetched live from OpenAlex

Commentary on: Mochamat, Cuhls H, Sellin J, et al . Fatigue in advanced disease associated with palliative care: a systematic review of non-pharmacological treatments. Palliat Med 2021; 35:697–709. doi: 10.1177/02692163211000628 Fatigue is reported as the principal concern in 5%–10% of primary care visits and a further 10% of family practice consultations. In the broader community, 5%–20% of the general population experience fatigue and almost half report its presence 1 year later.1 The majority of individuals with cancer experience fatigue (59%–100%), depending on disease progression and/or treatment regimes.2 While 80% of individuals living with fatigue rate it as significant to …

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.078
GPT teacher head0.367
Teacher spread0.289 · 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.

Study designObservational
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

Citations0
Published2021
Admission routes1
Has abstractyes

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