Pathologic Correlation of Posterior Ligamentous Injury With MRI
Bibliographic record
Abstract
This article describes 2 cases of spinal trauma in which diagnostic magnetic resonance imaging (MRI) was correlated with histopathology for diagnosis of a posterior ligamentous complex injury. Spine fractures are common and represent up to 16% of traumatic fractures. Diagnostic imaging currently involves plain films and computerized tomography, but MRI is being used with increasing frequency. The definition of neurologic tissue injury has had substantial documentation in the spinal literature. Clinically, posterior ligamentous complex injury has been associated with facet disruption, gapping of the spinous processes, and significant kyphosis. Assessment of spinal stability in the spine trauma population is based significantly on the assumed disruption or integrity of the posterior ligamentous complex. High signal intensity in the area of the ligamentum flavum and interspinous ligament on fat-saturated T2 MRIs has been associated with the clinical finding of interspinous ligament disruption noted at surgical exploration. Magnetic resonance imaging in spine trauma is widely accepted despite a paucity of data addressing its histopathologic accuracy. To our knowledge, histopathologic correlation of MRI of ligamentous injuries has not been reported.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".