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Performance of Adults After Stroke with and Without Aphasia on Neupsilin-L

2023· article· en· W4388884354 on OpenAlexaff
Joice Dickel Segabinazi, Maxciel Zortéa, Luciene Lima dos Santos Garay, Denise Ren da Fontoura, Jerusa Fumagalli de Salles, Jaqueline de Carvalho Rodrigues

Bibliographic record

VenuePsicologia - Teoria e Prática · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsInstitute of Particle Physics
FundersFundação para a Ciência e a TecnologiaFundação de Amparo à Pesquisa do Estado do Rio Grande do Sul
KeywordsAphasiaStroke (engine)PsychologyMedicinePhysical medicine and rehabilitationAudiologyNeuroscienceEngineering

Abstract

fetched live from OpenAlex

Analisaram-se as propriedades psicométricas preliminares do Instrumento de Avaliação Neuropsicolinguística Breve NEUPSILIN-L, em pacientes com e sem afasia expressiva. Participaram 94 adultos, sendo 11 com lesão cerebral no hemisfério direito (LHD), 38 no hemisfério esquerdo (LHE) e 45 neurologicamente saudáveis. O grupo com LHE apresentou os menores escores, principalmente nas tarefas de linguagem, em relação aos demais grupos, assim como a amostra com afasia. Grupos clínicos apresentaram melhor desempenho no NEUPSILIN-L nas tarefas com opções de resposta motora, em relação às respostas orais. Os itens do NEUPSILIN-L apresentaram alpha de Cronbach de alpha de Cronbach de 0,931e ômega de McDonald de 0,950. Os resultados dos grupos no NEUPSILIN-L demonstraram que o instrumento apresenta evidências de validade baseadas na relação com critério e alta consistência interna. Estudos futuros pretendem ampliar as evidências de validade do instrumento e oferecer dados normativos para a população brasileira.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.253
Teacher spread0.233 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2023
Admission routes1
Has abstractyes

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