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Origens do carcinoma mucoepidermoide central: revisão sistemática

2021· article· pt· W3160879978 on OpenAlexaboutno aff
Khalil Abdo Kansou, Mozarth Matheus Silvino do Nascimento, Elaine Rossi Ribeiro

Bibliographic record

VenueRevista de Medicina · 2021
Typearticle
Languagept
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCarcinomaPathology

Abstract

fetched live from OpenAlex

O carcinoma mucoepidermoide é um tumor maligno geralmente associado a glândulas salivares. Apenas de 2-4% de todos os carcinomas mucoepidermoides apresentam sítio primário intraósseo (carcinoma mucoepidermoide central), cuja etiogenia permanece obscura, justificando a importância de se pesquisar o assunto. Objetivo: Conhecer a(s) etiologia(s) mais provável(is) do carcinoma mucoepidermoide intraósseo. Método: revisão sistemática de acordo com as recomendações do PRISMA (Preferred Reporting itens for Systemstic Review and Meta-analysis Statement). As bases de dados consultadas foram: PubMed, Portal CAPES e Google acadêmico, e após aplicação dos critérios de inclusão e exclusão foram selecionados sete artigos que atenderam o objetivo da pesquisa, para os quais aplicaram-se a ferramenta Newcastle-Ottawa para análise de risco de viés e qualidade metodológica. A busca, seleção, extração e risco de viés foram feitas por três pesquisadores independentes Resultados: São duas as principais hipóteses etiológicas do carcinoma mucoepidermoide intraósseo: (1) derivado de um cisto odontogênico e (2) derivado de restos ectópicos. Conclusões: Ao que as evidências indicam o potencial pluripotente de células contidas nos cistos odontogênicos seria o responsável pela metaplasia e posterior carcinogênese. Nos casos derivados de restos ectópicos é clara a associação com a translocação t(11;19) e o transcrito de fusão CTRC1-MAML2 como um evento precoce ou etiológico.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.290
Teacher spread0.265 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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