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Record W2141548785 · doi:10.1123/jpah.2011-0316

Effects of Physical Activity on Breast Cancer Prevention: A Systematic Review

2014· review· en· W2141548785 on OpenAlexaboutno aff
Ana Katherine Gonçalves, Gilzandra Lira Dantas Florêncio, Maria José Maissonnete de Atayde Silva, Ricardo Ney Cobucci, Paulo César Giraldo, Nancy Côté

Bibliographic record

VenueJournal of Physical Activity and Health · 2014
Typereview
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerOdds ratioCohort studyConfidence intervalCINAHLMeta-analysisObservational studyCohortPopulationCancerInternal medicineOncologyEnvironmental healthPsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Observational studies have reported an association between physical activity and breast cancer risk reduction. This study aims to evaluate the effect of physical activity on breast cancer prevention. METHODS: Articles were identified through literature available on Electronic databases (PubMed, Embase, Scielo, Cochrane, CINAHL, Cancerlit, and Google Scholar) and manual searches. Case control and cohort studies were assessed for methodological quality, using the Newcastle-Ottawa scale. RESULTS: Size, population, components, and characteristics of physical activity, and menopausal status were documented. Review Manager 5.1 performed analysis using the statistical method of Mantel-Haenszel. Fixed-effect analysis with dichotomous data, testing subgroups and calculating odds ratio with a confidence interval of 95% were used. MAIN RESULTS: 7 cohort studies and 14 case control studies were evaluated. Statistical evidence found that physical activity reduces the risk of breast cancer in case-control studies [OR = 0.84 (0.81-0.88)] (heterogeneity 72%) and cohort studies [OR = 0.61 (0.59-0.63)] (heterogeneity 100%). CONCLUSION: Physical activity seems to prevent breast cancer mainly in postmenopausal women.

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)0.001
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: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0120.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.075
GPT teacher head0.455
Teacher spread0.380 · 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 designSystematic review
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

Citations81
Published2014
Admission routes1
Has abstractyes

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