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Record W4400290197 · doi:10.34119/bjhrv7n4-007

O impacto da cirurgia plástica estética nas mulheres

2024· article· pt· W4400290197 on OpenAlexaff
Bianka Vitaliano Zad, Juliana Ferreira de Alencar, Juliana Fogaça Maricato, Gislaine Alves da Silva, Kaline Silva Meneses

Bibliographic record

VenueBrazilian Journal of Health Review · 2024
Typearticle
Languagept
FieldSocial Sciences
TopicPhysical Education and Gymnastics
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesPsychologyMedicinePhilosophy

Abstract

fetched live from OpenAlex

A cirurgia plástica pode ter várias finalidades, como por exemplo restaurar alguma parte do corpo, ou reestabelecer a função e forma de partes do corpo afetados por problemas adquiridos ou congênito. A cirurgia plástica estética modela partes do corpo com o objetivo de melhorar a autoestima e beleza. Sendo assim, esse estudo irá abordar o impacto que as cirurgias plásticas estéticas tem na autoestima da mulher. Trata-se de uma revisão integrativa da literatura que consiste em resumos críticos de determinado tema com relevância na área de pesquisa, para sintetizar pesquisas anteriores a fim de conhecer e sugerir melhorias sobre determinado assunto. Os procedimentos estéticos mais procurados pelas mulheres nascem da insatisfação com o próprio corpo, que podem ser atrelados a gravidez, excesso de gordura e excesso de pele abdominal, o que afeta dentre outros fatores, a autoestima. Por se tratar de procedimentos que se obtém o resultado desejado em pouco tempo, gera satisfação com a aparência, o que melhora a autoimagem e proporciona sentimentos de felicidade. Dado os fatos expostos e analisados, a cirurgia plástica estética influencia a autoestima da mulher e relações sociais.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.420
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.094
GPT teacher head0.469
Teacher spread0.375 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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