Efficacy classification of modern therapies in multiple sclerosis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The Association of British Neurologists (ABN) 2015 guidelines suggested classifying multiple sclerosis therapies according to their average relapse reduction. We sought to classify newer therapies (cladribine, ocrelizumab, ofatumumab, ozanimod) based on these guidelines. Materials & methods: Therapies were classified by using direct comparative trial results as per ABN guidelines and generating classification probabilities for each therapy based on comparisons versus placebo in a network meta-analysis for annualized relapse rate. Results: For both approaches, cladribine and ofatumumab were classified as high efficacy. Ocrelizumab and ozanimod (1.0 mg) were classified as moderate or high efficacy depending on the approach used. Conclusion: Cladribine and ofatumumab have an efficacy comparable with therapies classified in the ABN guidelines as high efficacy.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it