Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To assess the relationship between regional brain volume changes and traumatic brain injury (TBI) severity in patients with and without focal lesions. METHODS: Sixty-nine chronic-phase TBI patients spanning the full range of severity were recruited from consecutive hospital admissions. Patients received high-resolution structural MRI a minimum of 1 year after injury. Multivariate statistical analyses assessed covariance patterns between volumes of gray matter, white matter, and sulcal/subdural and ventricular CSF across 38 brain regions and TBI severity as assessed by depth of coma at the time of injury. Patients with diffuse and diffuse plus focal injury were analyzed both separately and together. RESULTS: There was a stepwise, dose-response relationship between parenchymal volume loss and TBI severity. Patients with moderate and severe TBI were differentiated from those with mild TBI, who were in turn differentiated from noninjured control subjects. A spatially extensive pattern of volume loss covaried with TBI severity, with particularly widespread effects in white matter volume and sulcal/subdural CSF. The most reliable effects were observed in the frontal, temporal, and cingulate regions, although effects were observed to varying degrees in nearly every brain region. Focal lesions were associated with greater volume loss in frontal and temporal regions, but volume loss remained marked even when analyses were restricted to patients with diffuse injury. CONCLUSIONS: Patterns of parenchymal volumetric changes can differentiate among levels of traumatic brain injury (TBI) severity, even in mild TBI. TBI causes a spatially extensive pattern of volume loss that reflects independent but overlapping contributions of focal and diffuse injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it