Imaging Markers of Progression in Parkinson's Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is the second-most common neurodegenerative disorder after Alzheimer's disease; however, to date, there is no approved treatment that stops or slows down disease progression. Over the past decades, neuroimaging studies, including molecular imaging and MRI are trying to provide insights into the mechanisms underlying PD. METHODS: This work utilized a literature review. RESULTS: It is now becoming clear that these imaging modalities can provide biomarkers that can objectively detect brain changes related to PD and monitor these changes as the disease progresses, and these biomarkers are required to establish a breakthrough in neuroprotective or disease-modifying therapeutics. CONCLUSIONS: Here, we provide a review of recent observations deriving from PET, single-positron emission tomography, and MRI studies exploring PD and other parkinsonian disorders.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it