TEFREP: Épreuve de répétition de phrases en franco-québécois. Développement, validation et normalisation
Bibliographic record
Abstract
Sentence repetition is part of the assessment tasks used to better characterise aphasic patients' oral production. Moreover, impaired sentence and phrase repetition is a core feature of the logopenic variant of primary progressive aphasia. The aim of this study is to present the TEFREP (TEst Français de RÉpétition de Phrases), a French sentence repetition task that manipulates psycholinguistic variables known to affect the performance of aphasic patients. The final version of the TEFREP consists of 24 sentences in which length, semantic reversibility and type of sentence have been manipulated. The task shows good psychometric properties (validity and reliability). Norms according to age and education level have been developed from a sample of 80 healthy adults and older adults. In conclusion, the TEFREP fulfills the current need for a reliable assessment tool of sentence repetition in Canadian French-speaking populations and contributes to the differential diagnosis of language impairment.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".