A Voxel Based Morphometric Analysis of Longitudinal Cortical Gray Matter Changes in Progranulin Mutation Carriers At-Risk for Frontotemporal Dementia: Preliminary Study
Bibliographic record
Abstract
Frontotemporal dementia (FTD) is the second most common cause of dementia in those under 65, and is clinically characterized by progressive behavior change, executive dysfunction and language difficulties. Approximately 40% of subjects have a family history and an autosomal dominant pattern of inheritance.1,2 The three most common mutations are the microtubule-associated protein tau gene,3 the progranulin (PGRN) gene,4-6 and the C9ORF72. A number of studies have characterized the imaging features of these mutation-carriers. Whitwell et al.7 assessed gray matter (GM) atrophy in FTD patients with PGRN mutations and compared them to FTD without PGRN mutations using voxel based morphometry (VBM) technique. They found that the PGRN carriers showed significantly more frontal and parietal GM loss than the PGRN non-carriers. Other studies also implicated the parietal lobe as being more A Voxel Based Morphometric Analysis of Longitudinal Cortical Gray Matter Changes in Progranulin Mutation Carriers At-Risk for Frontotemporal Dementia: Preliminary Study
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".