A scan without evidence is not evidence of absence: Scans without evidence of dopaminergic deficit in a symptomatic leucine‐rich repeat kinase 2 mutation carrier
Bibliographic record
Abstract
INTRODUCTION: The basis for SWEDD is unclear, with most cases representing PD mimics but some later developing PD with a dopaminergic deficit. METHODS: We studied a patient initially diagnosed with SWEDD (based on (18)F-dopa PET) who developed unequivocal PD associated with a leucine-rich repeat kinase 2 p.G2019S mutation. Repeat multitracer PET was performed at 17 years' disease duration, including (+)[11C]dihydrotetrabenazine, [11C](N,N-dimethyl-2-(2-amino-4-cyanophenylthio) benzylamine (which binds the serotonin transporter), and (18)F-dopa. RESULTS: The patient showed bilateral striatal dopaminergic denervation (right putamen 28% of age-matched normal, left putamen 33%). (18)F-dopa uptake was decreased, particularly on the left (mean 31% of normal vs. 45% on the more affected right side). Serotonin transporter binding was relatively preserved in the putamen (right mean 90% of normal, left 81%) and several cortical regions. CONCLUSIONS: SWEDD can occur in genetically determined PD and may, in some cases, be the result of compensatory nondopaminergic mechanisms operating in early disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".