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Medidas eletrencefalográficas durante a aprendizagem de tarefa motora sob efeito do bromazepam

2005· article· pt· W2094304787 on OpenAlexaff
Víctor Hugo Bastos, Dionis Machado, Marlo Cunha, Cláudio Elidio Portella, Maurício Cagy, Vernon Furtado, Roberto Piedade, Pedro Ribeiro

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2005
Typearticle
Languagept
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsCanadiana.org
Fundersnot available
KeywordsBromazepamPsychologyHumanitiesPhysicsMedicineArtInternal medicine

Abstract

fetched live from OpenAlex

Neuromoduladores alteram constantemente as relações neurais pré-existentes no sistema nervoso. O bromazepam é utilizado com freqüência na prática clínica para diminuir padrões de ansiedade. Poucos são os experimentos correlacionando este ansiolítico às tarefas motoras. Neste contexto, o presente experimento visa analisar as alterações motoras e eletrocorticais decorrentes da administração de diferentes doses de bromazepam mediante a prática motora, e relacionar o efeito da droga a performance motora mão-dominante versus não dominante. Sujeitos saudáveis (39), de ambos os sexos, entre 20 a 30 anos compuseram a amostra. Os grupos controle (placebo) e experimental (bromazepam de 3mg e 6mg) foram treinados na tarefa de datilografia num modelo duplo-cego randomizado. Resultados do teste Stroop (atenção) não demonstraram diferenças no escore bruto e no tempo de execução do mesmo. Em contrapartida, nos resultados comportamentais foram observados um efeito principal entre blocos nas variáveis tempo de execução e erros cometidos durante a pratica motora. Os dados eletrofisiológicos evidenciaram interações significantes para: lateralidade/condição/momento; lateralidade/condição; lateralidade/momento; condição/momento; condição/setor.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.364
Teacher spread0.283 · 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 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

Citations11
Published2005
Admission routes1
Has abstractyes

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