Microstructural white matter changes underlying speech deficits in Parkinson’s disease
Bibliographic record
Abstract
Speech impairments are one of the common symptoms of individuals with Parkinson's disease (PD). However, little is known about the underlying neuroanatomical structural deficits specifically in the basal ganglia-thalamocortical (BGTC) loop in the speech deficits of PD. Here we investigated white matter differences in PD using probabilistic tractography. Diffusion tensor imaging data were downloaded from the Parkinson's Progression Markers Initiative database. We included three groups of participants: 20 PD individuals with speech deficits, 20 PD individuals without speech deficits, and 20 age- and gender-matched control participants. Overall, PD individuals with speech deficits had higher mean diffusivity in the BGTC pathway in the left hemisphere compared with PD individuals without speech deficits. The present study exhibits that there may be a distinct pathophysiological profile of white matter for speech deficits in PD.
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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) | 0.001 | 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".