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Record W2170781832

The influence of rehabilitation (kinesiotherapy) on the quality of life of cancer patients provided with palliative care

2007· article· en· W2170781832 on OpenAlexaboutno aff
Magdalena Grzybek, Alicja Mularczyk, Andrzej Ostrowski, Małgorzata Krajnik

Bibliographic record

VenueAdvances in Palliative Medicine · 2007
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsRehabilitationQuality of life (healthcare)Palliative careMedicineTerminal cancerPhysical therapyCancerDiseaseBalance (ability)Nursing
DOInot available

Abstract

fetched live from OpenAlex

Rehabilitation provision for the palliative patient is of great importance to the process of symptom treatment. It minimizes the complications and effects of the disease and optimizes, at least in the short term, the patients’ level of physical condition and both psychological and social functions. The aim of this study was to evaluate the influence of rehabilitation on patients’ quality of life in the terminal phases of cancer. The study involved 15 patients with advanced cancer and limited physical conditions. The Edmonton Functional Assessment Tool (EFAT) was used to measure the quality of life and control the symptoms. During the 28-day study significant improvement was observed in over 50% of the patients in the following: balance, mobility, activities of daily living and motivation, which are inseparable elements of improving the quality of life.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
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)0.0010.000

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 head0.020
GPT teacher head0.382
Teacher spread0.362 · 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 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

Citations3
Published2007
Admission routes1
Has abstractyes

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