Bibliographic record
Abstract
One of the challenges in developing a strategy for modifying the inexorable progression of neurodegenerative disorders like Parkinson disease (PD) is to develop practical methods to detect pathologic changes prior to the onset of symptoms in appropriate individuals. Functional neuroimaging with PET may be helpful in this regard. Tracers such as 6-[18F]fluoro-l-dopa (FDOPA) or [11C]dihydrotetrabenazine bind to presynaptic dopaminergic nerve endings. Studies in PD with these compounds consistently demonstrate a characteristic rostrocaudal gradient of decreased striatal tracer uptake corresponding to the pattern of presynaptic dopaminergic nerve terminal dysfunction. This technique has been extended successfully to studies of asymptomatic individuals who are thought to be at risk for the development of PD. Subclinical dysfunction in the nigrostriatal dopamine system has been demonstrated in asymptomatic subjects exposed to MPTP1 and in subjects with a high genetic risk of PD.2 While the underlying etiology of the majority of cases of PD is unknown, there is evidence that exposure to manganese, even at relatively low levels, can result in a spectrum of neurologic …
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.009 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".