Scale for the assessment and rating of ataxia: Development of a new clinical scale
Bibliographic record
Abstract
Objective: To investigate the cytokine-related molecular cascade leading to neural cell death in periventricular leukomalacia (PVL).Methods: The authors explored potential tumor necrosis factor ␣ (TNF␣) signaling pathways in human brains with PVL and conducted in situ immunohistochemical investigations to search for possible expression of cytokine receptors in these brains.They also investigated likely links to molecules potentially involved in neurocytotoxicity, particularly pathways involving nitrosative-induced apoptosis.Results: TNF␣ overexpression was associated with immune reactivity for p75TNF␣R2 and p55TNF␣R1 receptors in affected PVL areas.p75TNF␣R2 labeling was intense on cerebrovascular endothelial cells in PVL areas, whereas no vascular p55TNF␣R1 immunoreactivity was detected therein.Immune labeling for both receptors was detected on many white matter parenchymal cells.In contrast, there was no immune reactivity for either receptor in tissues taken from non-PVL areas.Additionally, in situ overexpression of inducible nitric oxide synthase was found in PVL brain regions where apoptotic cell death was detected.Conclusions: Both p75TNF␣R2 and p55TNF␣R1 receptors and nitric oxide may be implicated in the pathogenesis of periventricular leukomalacia.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".