Mapping metals in Parkinson's and normal brain using rapid-scanning x-ray fluorescence
Bibliographic record
Abstract
Rapid-scanning x-ray fluorescence (RS-XRF) is a synchrotron technology that maps multiple metals in tissues by employing unique hardware and software to increase scanning speed. RS-XRF was validated by mapping and quantifying iron, zinc and copper in brain slices from Parkinson's disease (PD) and unaffected subjects. Regions and structures in the brain were readily identified by their metal complement and each metal had a unique distribution. Many zinc-rich brain regions were low in iron and vice versa. The location and amount of iron in brain regions known to be affected in PD agreed with analyses using other methods. Sample preparation is simple and standard formalin-fixed autopsy slices are suitable. RS-XRF can simultaneously and non-destructively map and quantify multiple metals and holds great promise to reveal metal pathologies associated with PD and other neurodegenerative diseases as well as diseases of metal metabolism.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".