Paraneoplastic encephalitis: clinically based approach on diagnosis and management
Bibliographic record
Abstract
Paraneoplastic neurological syndromes (PNSs) comprise a subset of immune-mediated nervous system diseases triggered by an underlying malignancy. Each syndrome usually shows a distinct clinical presentation and outcome according to the associated neural antibodies. PNSs generally have a subacute onset with rapid progression and severe neurological disability. However, some patients may have hyperacute onset or even show chronic progression mimicking neurodegenerative diseases. Updated diagnostic criteria for PNS have been recently established in order to increase diagnostic specificity and to encourage standardisation of research initiatives related to PNS. Treatment for PNS includes oncological therapy and immunomodulation to halt neurological deterioration although current treatment options are seldom effective in reversing disability. Nevertheless, growing knowledge and better understanding of PNS pathogenesis promise better recognition, earlier diagnosis and novel treatment strategies. Considering that PNSs provide a model of effective anticancer immunity, the impact of these studies will extend far beyond the field of neurology.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".