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Record W2013853118 · doi:10.2147/tcrm.s30947

An update of teriflunomide for treatment of multiple sclerosis

2013· article· en· W2013853118 on OpenAlexaff
Paul O’Connor, Oh

Bibliographic record

VenueTherapeutics and Clinical Risk Management · 2013
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsTeriflunomideMedicineMultiple sclerosisClinical trialContext (archaeology)Investigational DrugsDiseaseIntensive care medicineAlternative medicinePharmacologyMedical physicsFingolimodInternal medicinePathologyImmunology

Abstract

fetched live from OpenAlex

There are a number of oral agents emerging as potential disease-modifying agents in multiple sclerosis (MS). Among these investigational agents, teriflunomide has shown promise in large, multicenter, phase III clinical trials with respect to safety and efficacy in relapsing MS patients, and is the latest disease-modifying agent approved for use in MS patients in the United States. This review will summarize teriflunomide's historical development, clinical pharmacology, studies in animals, clinical trials, and safety data, and will end with a discussion of the role of teriflunomide in MS in the context of existing treatment options.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.164
GPT teacher head0.407
Teacher spread0.243 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations38
Published2013
Admission routes1
Has abstractyes

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