Assessing Syntax Comprehension in French Post-Stroke Aphasic Patients : Developpement, Validation and Normalisation of The Batterie Du2019U00C9Valuation De La Compru00C9Hension Syntaxique (Bcs)
Bibliographic record
Abstract
Introduction: In order to fill a lack of clinical tools in French for evaluation of syntax processing, the Batterie du2019u00e9valuation de la compru00e9hension syntaxique (BCS) was developed in a collaborative work between research teams from Switzerland and Quebec. The BCS contains 5 sub-tests and is based on a cognitive syntax processing model.Methodology: For validation, a group of aphasic participants (n=30) was recruited to perform convergent, divergent and discriminant validity assessments and test-retest reliability. The sentence comprehension task of the MT-86 (the most commonly used french clinical test) was used as a reference. For normalisation, two groups of healthy participants from Switzerland (n=75) and Quebec (n=25) were recruited. Analyses were performed to compare the impact of geographic origin, age, and education on performance at BCS. Finally, the normative data for each BCS sub-test was calculated.Results: The BCS demonstrates good convergent validity, excellent divergent validity and excellent test-retest reliability. Discriminant validity analyses reveal that the BCS is as specific as the MT-86, but more sensitive in identifying post-stroke patients with syntax comprehension deficits. Control participants from Quebec and Switzerland perform similarly to the BCS. Only education level has a significant effect on performance; normative data is therefore stratified accordingly.Conclusion: The BCS has good metrological qualities and norms can be used with both Quebec-French and Swiss-French populations. Normative data, alert point (15th percentile) and cut-off (5th percentile) for each BCS sub-test, based on participantu2019s education level, were calculated and will be published shortly.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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 teacher head, 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".