Brief Montreal-Toulouse Language Assessment Battery: validity and reliability
Bibliographic record
Abstract
To present evidence of the validity and reliability of the Brief MTL-BR Battery, a screening tool for language assessment for people with aphasia (PWA). The sample consisted of 138 participants, including 96 neurologically healthy adults and 42 individuals with aphasia. Construct validity was investigated through convergent validity. To examine convergent validity, correlations between the Brief MTL-BR and the Montreal Toulouse Language Assessment Battery - MTL-BR tasks were used. Criterion validity was determined using Holm-Bonferroni to compare people with aphasia and healthy adults. Reliability was determined through inter-rater (Interclass Correlation Coefficients), the test-retest method (Interclass Correlation Coefficients), and internal consistency (Cronbach’s Alpha). The Brief MTL-BR demonstrated satisfactory construct validity, with correlation coefficients ranging from substantial to very strong (0.553 to 0.862). The assessment of criterion validity demonstrated significant differences between neurologically healthy adults and people with aphasia on all tasks examined. Reliability assessments revealed excellent inter-rater agreement (0.972 to 1). All tasks in the Brief MTL-BR Battery displayed Cronbach’s alpha values above 0.88. Significant correlations between tasks and retest scores were identified ranging from good to excellent (0.752 to 0.967). The present findings support the reliability and validity of the Brief MTL-BR Battery.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".