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Record W4392295452 · doi:10.47820/recima21.v5i2.4950

ESCLEROSE MÚLTIPLA - ABORDAGENS DIAGNÓSTICAS E TERAPÊUTICAS: UMA REVISÃO BIBLIOGRÁFICA

2024· article· pt· W4392295452 on OpenAlexaff
Lucas Mainardo Rodrigues Bezerra, Fernando Akio Yamashita, Júlia Lorena Lacerda Ferreira Pinho, J. Sobrinho, Caio César Silva Rocha, Caio Breno Reis Pires, Gabriel Osaki Queiroz Urzedo, Cleidson De Morais Silva

Bibliographic record

VenueRECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218 · 2024
Typearticle
Languagept
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsDiscovery Air (Canada)Alberta University of the Arts
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Introdução: A esclerose múltipla (EM) é uma doença progressiva do sistema nervoso central com crescente prevalência global, representando um desafio para pacientes e profissionais de saúde. Este estudo visa abordar as recentes estratégias diagnósticas e terapêuticas para melhorar o manejo da EM. Objetivo: Fornecer uma visão abrangente das abordagens diagnósticas e terapêuticas da EM. Métodos: Realizou-se uma revisão bibliográfica dos últimos 15 anos em bases de dados eletrônicas, utilizando critérios de inclusão específicos. Quinze artigos foram selecionados após avaliação de títulos e resumos. Resultados e Discussão: Destacou-se o aumento da incidência da EM globalmente e os avanços no diagnóstico, incluindo o papel da ressonância magnética e biomarcadores. Abordaram-se também as terapias convencionais e emergentes, enfatizando a importância da individualização do tratamento e da abordagem multidisciplinar. Conclusão: A pesquisa contínua e ensaios clínicos são essenciais para preencher lacunas de conhecimento. A abordagem centrada no paciente, combinada com avanços científicos, promete melhorar a qualidade de vida e os resultados clínicos na EM.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0070.018
Science and technology studies0.0030.003
Scholarly communication0.0040.001
Open science0.0030.004
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0080.013

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 head0.062
GPT teacher head0.374
Teacher spread0.312 · 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
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
Published2024
Admission routes1
Has abstractyes

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