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Record W2055503279 · doi:10.1517/14740338.6.3.279

The safety and efficacy of IFN-β products for the treatment of multiple sclerosis

2007· review· en· W2055503279 on OpenAlexaff
Marcelo Kremenchutzky, Sarah A. Morrow, Carolina Rush

Bibliographic record

VenueExpert Opinion on Drug Safety · 2007
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMedicineMultiple sclerosisAdverse effectClinical trialDiseaseDimethyl fumarateInternal medicineIntensive care medicineImmunology

Abstract

fetched live from OpenAlex

Multiple sclerosis, a chronic demyelinating disease of the CNS, is now a treatable disease. Phase III clinical trials of three recombinant IFN-beta products conducted in relapsing-remitting multiple sclerosis have shown, albeit modest, significant effects on relapses and short-term progression of disability, and a more substantial effect on MRI parameters. However, these effects do not correlate well with clinical disease activity or long-term disability. Overall, IFN-beta is safe and generally well tolerated, and reported adverse events were comparable between preparations. Systemic side effects can be effectively managed by dose escalation, use of an auto-injector and careful clinical monitoring.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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.

Opus teacher head0.201
GPT teacher head0.419
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations26
Published2007
Admission routes1
Has abstractyes

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