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Record W3002970851 · doi:10.1177/1352458519887324

Precision medicine in the multiple sclerosis clinic: Selecting the right patient for the right treatment

2020· review· en· W3002970851 on OpenAlexaff
Gauruv Bose, Mark S. Freedman

Bibliographic record

VenueMultiple Sclerosis Journal · 2020
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMultiple sclerosisMedicineDiseasePhysical therapyClinically isolated syndromeIntensive care medicinePediatricsInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is a chronic, inflammatory disease of the central nervous system (CNS), affecting patients of all ages, causing neurologic disability if inadequately treated. Some patients have a relatively benign disease course without significant disability after decades, while a more aggressive course ensues in others and disability progression occurs after only several years. Certain risk factors confer a higher chance of a patient having aggressive MS. Currently over 15 disease-modifying treatments (DMTs) are approved for MS with different efficacy and safety profiles. Deciding which DMT to use in a specific patient requires a careful analysis of a patient's disease course for high-risk factors for early progression, consideration of the efficacy and safety profile for potential therapy, as well as understanding of a patient's lifestyle and expectations. The integration of these factors is the art of precision medicine, a necessary practice in the treatment of patients with MS.

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)0.006
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.272
GPT teacher head0.396
Teacher spread0.124 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations27
Published2020
Admission routes1
Has abstractyes

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