MRI in traumatic spinal cord injury: from clinical assessment to neuroimaging biomarkers
Bibliographic record
Abstract
Traumatic spinal cord injury occurs when an external physical impact damages the spinal cord and leads to permanent neurological dysfunction and disability, and it is associated with a high socioeconomic burden. Conventional MRI plays a crucial role in the diagnostic workup as it reveals extrinsic compression of the spinal cord and disruption of the discoligamentous complex. Additionally, it can reveal macrostructural evidence of primary intramedullary damage such as haemorrhage, oedema, post-traumatic cystic cavities, and tissue bridges. Quantitative MRI, such as magnetisation transfer, magnetic resonance relaxation mapping, and diffusion imaging, enables the tracking of secondary changes across the neuraxis at the microstructural level. Both conventional MRI and quantitative MRI metrics, obtained early after spinal cord injury, are predictive of clinical outcome. Thus, neuroimaging biomarkers could serve as surrogate endpoints for more efficient future trials targeting acute and chronic spinal cord injury. The adoption of neuroimaging biomarkers in centres for spinal cord injury might lead to personalised patient care.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".