The Western Aphasia Battery: a systematic review of research and clinical applications
Bibliographic record
Abstract
Background: Since design and publication of the Western Aphasia Battery (WAB), increasing use to assess patients with aphasia in a clinical and research setting in stroke and in degenerative disease of the brain became evident. It has proven to be useful in determining the severity of and nature of the language impairment and providing clues for the location and function of the brain structures affected.Methods: Articles of WAB use were reviewed from the National Library of Medicine, Cochrane database under several headings of aphasia testing, stroke aphasia, primary progressive aphasia and others.Results: Available statistic indicated that the WAB is the most used comprehensive aphasia test. The overall severity score and quantitation of the components of the language impairment allows to define and classify aphasia, measure outcome in treatment modalities e.g., standard or constrained therapies, melodic intonation therapy, medications and transcranial stimulation and to study the linguistic features of aphasia and related cognition. Technological and scientific advances in neuroimaging from isotope scans to voxel-based morphometry, functional magnetic resonance and tractography uses the WAB for functional, anatomical and biological correlations of language.Conclusion: The acceptance of the WAB by researchers as well as clinicians appears to be related to the comprehensive measuring of essential and distinct language functions and practical length allowing it to be administered to a large variety of patients in diverse clinical and research conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".