Is there seasonal variation in risk of Parkinson's disease?
Bibliographic record
Abstract
Recent studies suggest that, for many adult-onset neurological diseases, persons born at a certain time of year are at higher risk of the disease. Small-scale studies have suggested that persons born in the spring may be at higher risk of developing Parkinson's disease (PD) late in life. There have also been suggestions that there are clusters of PD birth dates in the years of major influenza pandemics. To determine whether there is any seasonal variation in the birth dates of PD patients, we examined birth dates of 8,168 PD patients collected from subspecialty movement disorder clinics across Canada. Patterns of seasonality of birth were examined and compared with the general Canadian population. In addition, we compared counts of patients born in the years of major influenza pandemics with the number born in the surrounding years. We found no evidence of systematic seasonal variation in PD incidence by birth date, or of clustering of birth dates during influenza pandemic years in PD patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 teacher head, 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".