Quebec Parkinson Network Neuroimaging Cohort (QPN-NC)
Bibliographic record
Abstract
Data description: Quebec Parkinson Network Neuroimaging Cohort (QPN-NC) is a cross-sectional cohort of 202 individuals with PD and 69 older adults with multimodal MRI and extensive clinical and neuropsychological evaluations. The main objective of this data collection is to investigate neural correlates of motor and non-motor symptoms and facilitate comparisons with other PD studies. This QPN-NC release comprises well-characterized clinical assessments and curated imaging data processed through five neuroimaging pipelines. Additionally, we provide harmonized data annotations to facilitate search and cohort matching across other PD datasets. Data paper: Under review Data showcase: https://bic.neurobagel.org Data types: Imaging Raw Derivatives Tabular Demographics Assessments Data Access: Data requests can be made via this Zenodo page which will be reviewed by the data owners. Please read the data usage agreement and license details below before submitting the request. Data usage agreement: In progress
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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; both teacher heads agree on what is shown here.
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".