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Record W2055021279 · doi:10.14740/jnr.v4i1.235

Progressive Multifocal Leukoencephalopathy and Rituximab: Time to Better Stratify the Risk?

2014· article· en· W2055021279 on OpenAlexvenueno aff
Paolo Immovilli, Rota Eugenia, Morelli Nicola, De Mitri Paola, Emilio Terlizzi, Fabiola Magnifico, Luigi Cavanna, Maria Parmeggiani, Donata Guidetti

Bibliographic record

VenueJournal of Neurology Research · 2014
Typearticle
Languageen
FieldMedicine
TopicPolyomavirus and related diseases
Canadian institutionsnot available
Fundersnot available
KeywordsProgressive multifocal leukoencephalopathyMedicineNatalizumabRituximabDiseaseMultiple sclerosisRisk stratificationInternal medicineLeukoencephalopathyDemyelinating diseasePediatricsOncologyImmunologyLymphoma

Abstract

fetched live from OpenAlex

Progressive multifocal leukoencephalopathy (PML) is a demyelinating disease emerging as a complication of some novel monoclonal antibody therapies. Disease risk and severity show a wide variability, with fatality ranging from 30% to 90%, probably depending on many risk determinants as demonstrated for natalizumab-associated PML. Rituximab therapy is used to treat hematological malignancies and autoimmune disease, but little is known about PML risk stratification and management. We describe a clinical case with very early diagnosis, extensive treatment, but a fatal outcome, highlighting the need for future studies aimed to better understand PML risk. J Neurol Res. 2014;4(1):34-36 doi: http://dx.doi.org/ 10.14740 / jnr235w

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.002
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 head0.025
GPT teacher head0.353
Teacher spread0.328 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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