[Fingolimod in the treatment of multiple sclerosis. Novelties presented at the annual congress of the American Academy of Neurology (Toronto, April 2010)].
Bibliographic record
Abstract
Fingolimod, a sphingosine 1-phosphate receptor modulator, is currently on registration as an oral treatment for relapsing-remitting multiple sclerosis in the European Union and United States of America. New and important information on the drug was presented during the annual meeting of the American Academy of Neurology held in Toronto in April 2010, including, notably, results from the TRANSFORMS and FREEDOMS studies that, besides confirming the therapeutic benefit of the drug as a first-line therapy for multiple sclerosis, with superiority over interferon beta1a on clinical, inflammatory and functional outcomes, confirmed the safety and tolerability of the agent and described a specific benefit on the patients' functional abilities performing daily tasks. With additional new information on safety and tolerability and some new insight into the mechanism of action of fingolimod, new information presented during the meeting further supported the role of the drug in the treatment of multiple sclerosis and renewed hope for treating patients with a new therapeutic tool.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.015 |
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".