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DOENÇA TROFOBLÁSTICA GESTACIONAL: REVISÃO DE LITERATURA

2024· article· pt· W4400914418 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista Foco · 2024
Typearticle
Languagept
FieldMedicine
TopicGestational Trophoblastic Disease Studies
Canadian institutionsCentre Intégré de Santé et de Services Sociaux des Laurentides
Fundersnot available
KeywordsMedicinePsychology

Abstract

fetched live from OpenAlex

A doença trofoblástica gestacional (DTG) é dividida em um amplo grupo de alterações que vem a partir dos tecidos que revestem as velocidades corais, isto é, o trofoblasto, visto que se multiplica de forma anormal anatomopatologicamente. Dessa maneira, a DTG é classificada em formas benignas, que compreendem as molas hidatiformes completa e parcial, e malignas, ou seja, a neoplasia trofoblástica gestacional (NTG), que são divididas em coriocarcinoma gestacional, tumor trofoblástico do sítio placentário e tumor trofoblástico epitelioide. O objetivo deste trabalho é investigar os principais aspectos clínicos e patológicos da DTG por meio de uma revisão abrangente da literatura científica, diferenciando as formas benignas e invasoras, bem como analisando o impacto do beta-hCG para o diagnóstico e o prognóstico dessa patologia, além de compreender a patogênese e o tratamento dela. Dessa maneira, a gestação com DTG apresenta riscos por causa das complicações que podem surgir e levar a desafios psicossociais com relação à gravidez e até mesmo a mortes da mãe e do feto. Nessa perspectiva, essa patologia deve ser abordada de forma multiprofissional, juntando o cuidado de toda a equipe para melhor prognóstico.

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.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.880
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.016
GPT teacher head0.312
Teacher spread0.297 · 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