The Uniform Cortex Sign: A Diagnostic Sign of Diffuse Cortical Injury on MR Imaging of the Brain at 1.5 T
Bibliographic record
Abstract
BACKGROUND: To introduce the "uniform cortex sign" (UCS) and evaluate its performance as a diagnostic test for the presence of diffuse cortical injury (DCI). METHODS: The study was approved by our institutional review board. Three experienced neuroradiologists were given a tutorial on the UCS. They were subsequently presented with 14 cases (7 control patients and 7 DCI patients with the UCS) in random order and asked to determine whether the UCS was present. Each case consisted of selected DWI, T2-weighted, and FLAIR images from unenhanced 1.5T MRI examinations. A consensus result for each case was determined by unanimity or majority rule. RESULTS: All control patients were correctly identified as normal by all neuroradiologists (7/7). The UCS was correctly identified in 86% of DCI patients (6/7). UCS interrater agreement was high (multirater κ=0.81). CONCLUSIONS: This small study shows that the UCS can identify DCI, especially in patients with hypoxic-ischemic encephalopathy. The UCS can be subtle, hence the reader must be vigilant for this finding. The accuracy of the UCS may depend on the extent of cortical injury and time between injury and MRI. Also, a UCS may be reversible, as in our case of viral meningoencephalitis.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".