The image of essential tremor: current neuroimaging and clues to disease localization, pathogenesis, and diagnosis
Bibliographic record
Abstract
This chapter focuses on the main findings and advances brought by magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to the understanding of prodromal and early-stage patients. In Huntington's disease (HD), as in many neurodegenerative disorders, accurate markers of disease progression that reflect pathogenic mechanisms are currently lacking, and therefore are an important focus of current research. MR techniques are a particularly promising tool in the identification of such biomarkers. Using MRI, cerebral blood flow (CBF) or perfusion can be quantitatively measured using a technique named arterial spin labeling (ASL). For measuring brain activity, another technique can be used, namely blood oxygen level-dependent (BOLD) imaging. MRI is based on the detection of the proton signal within water molecules. Finally, the chapter reviews new approaches used in animal models that will hopefully be translated in clinical studies in the near future.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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".