Bibliographic record
Abstract
Background and Aims 61-year-old lady case of Complex Regional Pain Syndrome involving the left foot and ankle due to Left foot crush injury (3-foot fractures/first proximal phalanx and first metatarsal). Her pain has been refractory to pharmacotherapy and SCS trial then she developed new symptoms and changes in the pain character as lower back and the left buttock radiating in the outer aspect of the left posterior thigh and radiating down the calf into the outer aspect of the foot and the sole of the foot. Urgent MRI showed: Multiple prominent bilateral perineural nerve root sleeve cysts that are Tarlov cysts within the sacral spinal canal tracking along with the proximal exiting nerve roots. Methods Results Tarlov cysts are an uncommon cause of back pain.Tarlov cysts are fluid-filled sacs that most often affect nerve roots at the lower end of the spine. Such cysts typically cause no symptoms and are found incidentally in magnetic resonance imaging (MRI) studies done for other reasons. (1) Conclusions in some cases, the cysts expand, putting pressure on the affected nerve root. The results may include sharp, burning pain in the hip and down the back of the thigh, possibly with weakness and reduced sensation all along the affected leg and foot. Tarlov cysts sometimes enlarge enough to cause erosion of the surrounding bone, which is another way they may cause back pain. In most cases, Tarlov cysts require no treatment. For those that do, some surgical treatments — such as draining the cyst, have had promising results. (1)
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".