Montreal-Toulouse Language Assessment Battery for aphasia: Validity and reliability evidence
Bibliographic record
Abstract
BACKGROUND: In Brazil, no standardized instruments are available to assess language in patients with aphasia. OBJECTIVE: The aim of the current study was to search for reliability and validity evidence for the Montreal-Toulouse Language Assessment Battery (MTL-BR). METHODS: The sample was composed of 537 adults, of whom 463 were healthy individuals and 74 had neurological lesions (25 participants had right hemisphere brain damage, 21 had left hemisphere damage (LHD) with aphasia and 28 had LHD without aphasia). Reliability was assessed by internal consistency (Cronbach's alpha) and test-retest analyses. Test-retest reliability was calculated using the Pearson correlation coefficient, and a repeated measures analysis of variance, with years of education as a covariate. Construct validity was verified by correlations between scores in MTL-BR subtest and similar tasks from other language assessment instruments. RESULTS: Internal consistency was satisfactory (Cronbach's alpha between 0.79 and 0.90), as were correlations between test and retest scores (mean 0.52), and between the MTL-BR and scores in similar instruments. CONCLUSIONS: The present results suggested that the MTL-BR battery had adequate reliability and validity as a method for diagnosing and monitoring aphasia.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".