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Record W4390004060 · doi:10.18616/inova.v13i3.8318

CARCINOMA LOBULAR INVASIVO DE MAMA: UM RELATO DE CASO

2023· article· pt· W4390004060 on OpenAlexaff
JULIA MANNRICH ROVEDA, Débora Dagostin Casagrande, Flávia Soldatelli Formighieri, Camila Pezente Dal Toe, ANDRE MANNRICH ROVEDA, RAFAELA BRUNA MACHADO

Bibliographic record

VenueInova Saúde · 2023
Typearticle
Languagept
FieldMedicine
TopicWomen's cancer prevention and management
Canadian institutionsNovelis (Canada)
Fundersnot available
KeywordsGynecologyMedicine

Abstract

fetched live from OpenAlex

Introdução: O carcinoma lobular invasivo (CLI) é um subtipo mais raro de câncer de mama que se origina nos lóbulos mamários, possuindo características clínicas distintas e fatores de risco mais relacionados a exposição hormonal. Relato de Caso: Este trabalho descreve o caso clínico de uma paciente de 62 anos, em uso terapia de reposição hormonal, que ao autoexame físico identificou uma massa palpável na mama direita. Os exames de imagem e a biópsia confirmaram o diagnóstico de CLI, caracterizado como moderadamente diferenciado e com receptores hormonais positivos. A paciente foi submetida à mastectomia total direita, além de tratamento quimioterápico e radioterápico adjuvante. Conclusão: Este relato de caso visa aumentar a compreensão do CLI, fornecendo informações relevantes sobre sua apresentação clínica, diagnóstico, tratamento e abordagem pratica dessa forma específica de câncer de mama. Palavras-chave: Câncer de mama; Carcinoma lobular; Terapia de Reposição Hormonal

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.032
GPT teacher head0.296
Teacher spread0.264 · 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 designCase report
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
Published2023
Admission routes1
Has abstractyes

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