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Record W2861714648 · doi:10.1016/s1474-4422(18)30202-3

Oral fingolimod for chronic inflammatory demyelinating polyradiculoneuropathy (FORCIDP Trial): a double-blind, multicentre, randomised controlled trial

2018· article· en· W2861714648 on OpenAlexaff
Richard AC Hughes, Marinos C. Dalakas, Ingemar S. J. Merkies, Norman Latov, Jean‐Marc Léger, Eduardo Nobile‐Orazio, Gen Sobue, Angela Genge, David R. Cornblath, Martin Merschhemke, Carolyn M. Ervin, Catherine Agoropoulou, Hans‐Peter Hartung, Timothy Day, Judith Spies, L. Jackson Roberts, Philip Van Damme, P Y Van den Bergh, Alain Maertens de Noordhout, Annie Dionne, Sandrine Larue, Rami Massie, Michel Melanson, William Camu, de Sèze, Gwendal Le Masson, Jean Pouget, Jens Schmidt, Vasilios Κ. Kimiskidis, Joab Chapman, Vivian E. Drory, Raffaella Fazio, Francesca Gallia, Susumu Kusunoki, Masahiro Mori, Masahiro Iijima, Tomoko Okamoto, Masayuki Baba, Catharina G. Faber, Ivo N. van Schaik, Waldemar Fryze, Ewa Motta, Krzysztof Selmaj, Carlos Casasnovas, A. Guerrero Sola, Isabel Illa, James Holt, James Miller, Michael P. Lunn, Thomas H. Brannagan, M. Brown, J Kelemen, Stanley Iyadurai, Kourosh Rezania, Khema R. Sharma, Rup Tandan, Mark Gudesblatt, V. Lawson, Anthony A. Amato

Bibliographic record

VenueThe Lancet Neurology · 2018
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMedicineFingolimodPolyradiculoneuropathyPlaceboExpanded Disability Status ScaleClinical endpointInternal medicineRandomized controlled trialPhysical therapyAdverse effectMultiple sclerosisPediatricsGuillain-Barre syndromeImmunologyAlternative medicine

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.001

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 head0.046
GPT teacher head0.320
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations74
Published2018
Admission routes1
Has abstractno

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