Evaluating the cerebral correlates of survival in amyotrophic lateral sclerosis
Bibliographic record
Abstract
Abstract Objective To evaluate cerebral degenerative changes in ALS and their correlates with survival using 3D texture analysis. Methods A total of 157 participants were included in this analysis from four neuroimaging studies. Voxel‐wise texture analysis on T1‐weighted brain magnetic resonance images (MRIs) was conducted between patients and controls. Patients were divided into long‐ and short‐survivors using the median survival of the cohort. Neuroanatomical differences between the two survival groups were also investigated. Results Whole‐brain analysis revealed significant changes in image texture (FDR P < 0.05) bilaterally in the motor cortex, corticospinal tract (CST), insula, basal ganglia, hippocampus, and frontal regions including subcortical white matter. The texture of the CST correlated (P < 0.05) with finger‐ and foot‐tapping rate, measures of upper motor neuron function. Patients with a survival below the media of 19.5 months demonstrated texture change (FDR P < 0.05) in the motor cortex, CST, basal ganglia, and the hippocampus, a distribution which corresponds to stage 4 of the distribution TDP‐43 pathology in ALS. Patients with longer survival exhibited texture changes restricted to motor regions, including the motor cortex and the CST. Interpretation Widespread gray and white matter pathology is evident in ALS, as revealed by texture analysis of conventional T1‐weighted MRI. Length of survival in patients with ALS is associated with the spatial extent of cerebral degeneration.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".