Bibliographic record
Abstract
Many women with multiple sclerosis (MS) ask about the risks of pregnancy before starting (or while on) disease-modifying therapies (DMTs). At least two-thirds of patients with MS are women, and the majority are in their childbearing years at the time of clinical onset and diagnosis. DMTs taken during pregnancy could have direct or indirect toxicity (through immunomodulating properties) on pregnancy outcome. High doses of interferon beta (IFNβ) are abortifacient in monkeys, but studies of teratogenicity in animals are limited by the rapid appearance of antibodies to human IFNβ (product information). Therefore, pregnancy outcome after in utero exposure to DMTs is important, particularly because DMTs are increasingly initiated early in the course of MS. In this issue of Neurology , two articles provide data on pregnancy outcome after in utero exposure to IFNβ.1,2 Sandberg-Wollheim et al.1 provide the first systematic and comprehensive analysis of pregnancy frequency and outcome, combining data from several randomized clinical trials of IFNβ-1a. Because allocation of treatment (IFNβ-1a at any dose vs …
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".