Anti-Ma2 Antibody-Mediated Paraneoplastic Cerebellar Degeneration and Myeloneuropathy Secondary to Lymphoma
Bibliographic record
Abstract
ABSTRACT: A 61-year-old woman with a history of untreated low-grade B-cell lymphoma presented with blurry vision, unsteadiness, and worsening pain on touching skin of the upper trunk was enrolled. Blurry vision was attributed to oscillopsia from downbeat nystagmus, which later evolved into macrosaccadic oscillations. MRI brain and spine showed mild, longitudinally extensive T2 hyperintensity in the central gray matter of the spinal cord extending from the medulla to T11 level. Serum paraneoplastic panel was negative; however, she had very high titers of anti-Ma2 antibodies in cerebrospinal fluid. The diagnosis of paraneoplastic neurological syndrome was made. Empiric treatment with high dose of intravenous steroids followed by intravenous immunoglobulin infusions did not improve her symptoms. An extensive search for an underlying tumor commenced and was initially unrevealing. However, two-month follow-up positron emission tomography scan showed increased uptake in a right pulmonary nodule, which when biopsied confirmed diagnosis of extranodal marginal zone lymphoma. The final diagnosis was anti-Ma2 antibody-mediated paraneoplastic cerebellar degeneration and myeloneuropathy secondary to lymphoma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".