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Record W3200887443 · doi:10.1007/s40263-021-00860-7

Natalizumab Versus Fingolimod in Patients with Relapsing-Remitting Multiple Sclerosis: A Subgroup Analysis From Three International Cohorts

2021· article· en· W3200887443 on OpenAlexaff
Sifat Sharmin, Mathilde Lefort, Johanna Balslev Andersen, Emmanuelle Leray, Dana Horáková, Eva Havrdová, Raed Alroughani, Guillermo Izquierdo, Serkan Özakbaş, Francesco Patti, Marco Onofrj, Alessandra Lugaresi, Murat Terzi, Pierre Grammond, François Grand’Maison, Bassem Yamout, Alexandre Prat, Marc Girard, Pierre Duquette, Cavit Boz, María Trojano, Pamela McCombe, Mark Slee, Jeannette Lechner‐Scott, Recai Türkoğlu, Patrizia Sola, Diana Ferraro, Franco Granella, Julie Prévost, Davide Maimone, Olga Skibina, Katherine Buzzard, Anneke van der Walt, Bart Van Wijmeersch, Tünde Csépány, Daniele Spitaleri, Steve Vucic, Romain Casey, Marc Debouverie, Gilles Edan, Jonathan Ciron, Aurélie Ruet, de Sèze, Élisabeth Maillart, Hélène Zéphir, Pierre Labauge, Gilles Defer, Christine Lebrun‐Frénay, Thibault Moreau, Éric Berger, Pierre Clavelou, Jean Pelletier, Bruno Stankoff, Olivier Gout, Éric Thouvenot, Olivier Heinzlef, A. Al-Khedr, Bertrand Bourre, Olivier Casez, Philippe Cabre, Alexis Montcuquet, Abir Wahab, Jean‐Philippe Camdessanché, Aude Maurousset, I. Patry, Karolina Hankiewicz, Corinne Pottier, Nicolas Maubeuge, Céline Labeyrie, Chantal Nifle, David Laplaud, N. Koch-Henriksen, Finn Sellebjerg, Per Soelberg Soerensen, Claudia Pfleger, Peter Vestergaard Rasmussen, Michael Broksgaard Jensen, Jette Lautrup Frederiksen, Stephan Bramow, Henrik Kahr Mathiesen, Karen Schreiber, Melinda Magyari, Sandra Vukusic, Helmut Butzkueven, Tomáš Kalinčík

Bibliographic record

VenueCNS Drugs · 2021
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsCegep de Saint JeromeUniversité de MontréalCentre Hospitalier de l’Université de MontréalCentre intégré de santé et de services sociaux de Chaudière-Appalaches
FundersNational Health and Medical Research CouncilAgence Nationale de la Recherche
KeywordsFingolimodMedicineNatalizumabExpanded Disability Status ScaleMultiple sclerosisInternal medicineConfidence intervalCohortHazard ratioDiseaseImmunology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
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 score0.012
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.036
GPT teacher head0.272
Teacher spread0.236 · 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

Citations12
Published2021
Admission routes1
Has abstractno

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