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Record W7065665701

EFECTIVIDAD DEL EJERCICIO FÍSICO PARA DISMINUIR LA FATIGA EN PACIENTES CON CÁNCER DE MAMA

2019· dissertation· es· W7065665701 on OpenAlexaboutno aff

Bibliographic record

Venuerenati · 2019
Typedissertation
Languagees
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyPhysical exerciseExercise therapyPhysical activityBreast cancer
DOInot available

Abstract

fetched live from OpenAlex

Objective: Systematize the evidence on the effectiveness of exercise to reduce fatigue in patients with cancer.Material and Methods: Observational and retrospective systematic review of quantitative type, subjected to critical selection, using the Grade evaluation system for the identification of the degree of evidence, found in the following databases: Pubmed, Liliacs, Scielo, Epistemonikos.The 10 articles reviewed systematically, 100% (n = 10/10) is a systematic review.In relation to the provenance of the evidence, 20% (2/10) are from China, 10% (1/10) from Ireland, 10% (1/10) from the United States, 10% (1/10) from Brazil., 10% (1/10) of Costa Rica, 10% (1/10) of Cyprus, 10% (1/10) of Canada, 10% (1/10) of Germany and 10% (1/10) of England.Results: 90% (n = 9/10) indicates that exercise is effective to reduce fatigue in patients with cancer.The 10% (n = 1/10) point out that physical exercise impresses not to decrease the levels of fatigue in women with breast cancer who present the symptom.Conclusion: Exercise is effective in reducing fatigue in patients with cancer.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.272
Teacher spread0.265 · 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 designBench or experimental
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
Published2019
Admission routes1
Has abstractyes

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