Longitudinal analysis highlights structural changes in grey- and white-matter within military personnel exposed to blast
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to determine whether gray matter volume and diffusion-based metrics in associated white matter changed in breachers who had neuroimaging performed at two timepoints. A secondary purpose was to compare these changes in a group who had a one-year interval between their imaging timepoints to a group that had a two-year interval between imaging. METHODS: Between timepoints, clusters with significantly different gray matter volume were used as seeds for reconstruction of associated structural networks using diffusion metrics. RESULTS: Of 92 eligible participants, 62 had imaging at two timepoints, 36 with a one-year interval between scans and 26 with a two-year interval between scans. A significant effect of time was documented in the midcingulate cortex, but there was no effect of timepoint (1 versus 2 years). The associated white matter in this cluster had three regions with differences in fractional anisotropy compared to baseline, while there was no effect of timepoint (1 versus 2 years). CONCLUSIONS: This study provides preliminary evidence that military personnel involved in repetitive exposure to sub-concussive blast overpressures may experience changes to both gray matter and white matter structures.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".