MétaCan
Menu
Back to cohort
Record W1973931332 · doi:10.1097/jnn.0000000000000039

Pegylated Interferons

2014· review· en· W1973931332 on OpenAlex
Anne Howley, Marcelo Kremenchutzky

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Neuroscience Nursing · 2014
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsPEGylationDosingMedicineBioavailabilityPharmacologyPolyethylene glycolMultiple sclerosisDrugPatient complianceEthylene glycolClinical trialPharmacokineticsPEG ratioPegylated interferonIntensive care medicineInternal medicineImmunologyChemistryVirusRibavirinEmergency medicine

Abstract

fetched live from OpenAlex

Most multiple sclerosis (MS) therapies are injectable drugs, and the frequency of injections has been shown to be inversely proportional to overall compliance. One method of improving therapeutic compliance and thus clinical outcomes is to develop medications that require less frequent dosing. One of the most promising modification techniques to extend the bioavailability of a drug is poly(ethylene glycol) conjugation (pegylation), which increases the size of a molecule by attaching polyethylene glycol moieties to the parent compound, resulting in slower clearance and metabolism. This approach has been used to improve the efficacy of a number of therapeutic molecules, including interferons. Peginterferon beta-1a, a pegylated form of interferon beta-1a, is currently in phase III clinical trials for relapsing MS and has the potential to improve patient compliance by reducing the number of injections while maintaining clinical efficacy. The role of nurses in educating patients about the effective use of this new MS therapy is discussed.

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 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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.235
GPT teacher head0.485
Teacher spread0.250 · 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