CJN volume 30 issue 1 Cover and Front matter
Bibliographic record
Abstract
Rebit relative benefits vs. Reduced Delayed relapse rate progression of disability §jfj §|#fgt 8i«aa»i (1.73 vs. 2.56 with placebo, (21.3 vs. 11.9 months with placebo, mean, p<0.005) first quartile, p<0.05, delay in time to confirmed first progression) placebo Reduced burden of disease (-3.8% vs. +10.9%with placebo, median, p< 0.0001, as measured by MR!) In two pivotal studies, including a total of 628 patients, Rebif showed significant efficacy in three major outcomes (relapses, disability progression and MRI).U Its ability to affect the course of the disease 2 has made Rebif not only a good first-line choice for relapsing-remitting MS, but the leading drug in Results of the 44 meg TIW dose at 2 years. 1 H-S CmSS.Rebif is generally well-tolerated.The most common adverse events are often manageable and decrease in frequency and severity over time.2t Rebif alters the natural course of relapsing-remitting MS. 2 Rebif" is indicated for the treatment of relapsing-remitting multiple sclerosis in patients with an EDSS between 0 and 5.0, to reduce the number and severity of clinical exacerbations, slow the progression of physical disability, reduce the requirement for steroids, and reduce the number of hospitalizations for treatment of multiple sclerosis.The efficacy of Rebif has been confirmed by Ti-Gd enhanced and T2 (burden of disease) MRI evaluations.2 t The most common adverse events reported are injection-site disorders (all) (92.4% vs. 38.5% placebo), upper respiratory tract infections (74.5% vs. 85.6% placebo), headache (70.1% vs. 62.6% placebo), flu-like symptoms (58.7% vs. 51.3%placebo), fatigue (41.3% vs. 35.8%placebo) and fever (27.7% vs. 15.5% placebo).Evidence of safety and efficacy derived from 2-year data only.Please see product monograph for full prescribing information.2 t Randomized, double-blind, placebo-controlled trial.Rebif 44 meg TIW group (n=184), Rebif 22 meg TIW group (n=189), placebo group (n=187).'A Fictitious case may not be representative of results for the general population. ~-.seronoInterferon b«ta-1aFOR MULTIPLE REASONS.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.738 | 0.479 |
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".