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Record W2134373973 · doi:10.1155/2012/356851

Risk and Protective Factors for Breast Cancer in Midwest of Brazil

2012· article· en· W2134373973 on OpenAlexaff
Lívia Emi Inumaru, Maira Quintanilha, Érika Aparecida Silveira, Maria Margareth Veloso Naves

Bibliographic record

VenueJournal of Environmental and Public Health · 2012
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBreast cancerMedicineOncologyEnvironmental healthInternal medicineCancer

Abstract

fetched live from OpenAlex

Patterns of physical activity, body composition, and breastfeeding are closely related to health and are influenced by environmental, economic, and social factors. With the increase of sedentary lifestyle and overweight, many chronic diseases have also increased, including cancer. Breast cancer is the most common cancer in women worldwide, and the knowledge of its risk and protective factors is important to the adoption of primary prevention strategies. We aimed to investigate some risk and protective factors for breast cancer among women from Midwest Brazil. It is a case-control study of outpatient basis, carried out with 93 breast cancer cases and 186 controls. Socioeconomic, gynecological, anthropometric, and lifestyle variables were collected, and odds ratios (ORs) values were estimated (significance level, 5%; confidence interval (CI), 95%). Per capita income equal to or lower than 1/2 Brazilian minimum wage (OR = 1.88; CI = 1.06-3.29), residence in rural area (OR = 4.93; CI = 1.65-14.73), and presence of family history of breast cancer (OR = 5.38; CI = 1.46-19.93) are risk factors for breast cancer. In turn, physical activity (past 6 months) (OR = 0.23; CI = 0.10-0.55) and leisure physical activity at 20 years old (OR = 0.13; CI = 0.03-0.54) are protective factors for the disease in women who live in Midwest of Brazil.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.022
GPT teacher head0.307
Teacher spread0.285 · 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.

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

Citations30
Published2012
Admission routes1
Has abstractyes

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