Cognitive inhibition impairments in presymptomatic <i>C9orf72</i> carriers
Bibliographic record
Abstract
OBJECTIVE: mutation carriers (C9+) and its associated neuroanatomical correlates. METHODS: mutation carriers (C9+, mean age 38.2±8.0 years) and 22 C9- controls from the PREV-DEMALS cohort were included in this study. They underwent a cognitive inhibition assessment with the Hayling Sentence Completion Test (HSCT; time to completion (part B-part A); error score in part B) as well as a 3D MRI. RESULTS: C9+ individuals younger than 40 years had higher error scores (part B) but equivalent HSCT time to completion (part B-part A) compared to C9- individuals. C9+ individuals older than 40 years had both higher error scores and longer time to completion. HSCT time to completion significantly predicted the proximity to estimated clinical conversion from presymptomatic to symptomatic phase in C9+ individuals (based on the average age at onset of affected relatives in the family). Anatomically, we found that HSCT time to completion was associated with the integrity of the cerebellum. CONCLUSION: The HSCT represents a good marker of cognitive inhibition impairments in C9+ and of proximity to clinical conversion. This study also highlights the key role of the cerebellum in cognitive inhibition.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".