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The Wada Test: contributions to standardization of the stimulus for language and memory assessment

2004· article· en· W2087055464 on OpenAlexaboutno aff
Maria Joana Mäder, Bellkiss Wilma Romano, Luciano de Paola, Carlos Eduardo Silvado

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2004
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsStimulus (psychology)StandardizationAudiologyPsychologyEpilepsyMemory testPopulationCognitive psychologyMedicineNeuroscienceComputer scienceCognition

Abstract

fetched live from OpenAlex

The Wada Test (WT) is part of the presurgical evaluation for refractory epilepsy. The WT is not standardized and the protocols differ in important ways, including stimulus type of material presented for memory testing, timing of presentations and methods of assessment. The aim of this study was to contribute to establish parameters for a WT to Brazilian population investigating the performance of 100 normal subjects, without medication. Two parallel models were used based on Montreal Procedure adapted from Gail Risse's (MEG-MN,EUA) protocol. The proportions of correct responses of normal subjects submitted to two parallel WT models were investigated and the two models were compared. The results showed that the two models are similar but significant differences among the stimulus type were observed. The results suggest that the stimulus type may influence the results of the WT and should be considered when constructing models and comparing different protocols.

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)0.006
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.009
GPT teacher head0.345
Teacher spread0.336 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations6
Published2004
Admission routes1
Has abstractyes

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