Follow-up evaluation with ultrasonography of peripheral nerve injuries after an earthquake
Bibliographic record
Abstract
Published data on earthquake-associated peripheral nerve injury is very limited. Ultrasonography has been proven to be efficient in the clinic to diagnose peripheral nerve injury. The aim of this study was to assess the role of ultrasound in the evaluation of persistent peripheral nerve injuries 1 year after the Wenchuan earthquake. Thirty-four patients with persistent clinical symptoms and neurologic signs of impaired nerve function were evaluated with sonography prior to surgical repair. Among 34 patients, ultrasonography showed that 48 peripheral nerves were entrapped, and 11 peripheral nerves were disrupted. There was one case of misdiagnosis on ultrasonography. The concordance rate of ultrasonographic findings with those of surgical findings was 98%. A total of 48 involved nerves underwent neurolysis and the symptoms resolved. Only five nerves had scar tissue entrapment. Preoperative and postoperative clinical and ultrasonographic results were concordant, which verified that ultrasonography is useful for preoperative diagnosis and postoperative evaluation of injured peripheral nerves.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".