Correlation of Pathological Findings with MRI Imaging in Traumatic Spinal Cord Injury in Hyperacute Time Period in Non Human Primate Model
Bibliographic record
Abstract
Traumatic Spinal Cord Injury (TSCI) remains a significant cause of human suffering. The World Health Organization estimates that there are between 250,000 to 500,000 new cases every year. Magnetic Resonance Imaging (MRI) has been an important advancement in the diagnosis and management of TSCI. Nevertheless, there is a lack of literature correlating the radiological abnormalities and histopathological findings in the first hour (i.e., hyperacute period) after injury. The aim of this preliminary study is to elucidate the relationship between the MRI abnormalities and histopathological abnormalities in the hyperacute time period. In this study, a non-human primate model (NHP) primate model is used to characterize the histopathological and radiological features. Specifically, an experimental TSCI is created with an epidural catheter. This is followed by MRI imaging. The subject is then humanely euthanized and a post-mortem examination is completed. These results suggest that the noted radiological abnormalities are consistent with a combination of hemorrhage, edema as well as eosinophilic cellular matter in the central canal.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".