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Record W4413894959 · doi:10.1002/mdc3.70323

Validation of the French Translation of the Movement Disorder Society Non‐Motor Symptoms Scale ( <scp>MDS</scp> ‐ <scp>NMS</scp> ) in Parkinson's Disease

2025· letter· en· W4413894959 on OpenAlexafffundabout
Clément Desjardins, Stéphan Grimaldi, Sheng Luo, Christopher G. Goetz, Glenn T. Stebbins, Pablo Martínez‐Martín, Mónica Kurtis, Tiago Mestre, Álvaro Sánchez‐Ferro, Michelle Hyczy de Siqueira Tosin, Roberta Balestrino, Chi‐Ying Lin, Carmen Gasca‐Salas, Tatiana Witjas, Olivier Colin, David Maltête, Luc Defebvre, Caroline Giordana, Mahmoud Charif, Claire Thiriez, Chloé Laurencin, Mélissa Tir, Gwendoline Dupont, Philippe Rémy, Christine Tranchant, Sophie Drapier, A. Foubert Samier, Isabelle Bénatru, Sara Sambin, Jean‐Christophe Corvol, Fatma Kelifi, Margherita Fabbri, Olivier Rascol

Bibliographic record

VenueMovement Disorders Clinical Practice · 2025
Typeletter
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsParkinson's Clinic of Eastern Toronto & Movement Disorders CentreUniversity of Ottawa
FundersServierUniversité de ToulouseNeurocrine BiosciencesFondation Brain CanadaAssociation France ParkinsonComunidad de MadridCanadian Institutes of Health ResearchParkinson CanadaH. Lundbeck A/SSunovionOttawa Hospital Research InstituteInstituto de Salud Carlos IIIRush UniversityAlzheimer's AssociationMultiple System Atrophy CoalitionBoston Scientific CorporationTeva Pharmaceutical IndustriesPfizerBiogenInternational Parkinson and Movement Disorder SocietyCHDI FoundationEli Lilly and CompanyAcorda TherapeuticsUniversity of Ottawa
KeywordsParkinson's diseaseMovement disordersNeuroscienceMovement (music)Motor symptomsDiseasePhysical medicine and rehabilitationPsychologyMedicineInternal medicinePhilosophy

Abstract

fetched live from OpenAlex

on behalf of the NS-Part

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 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)0.021
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.003

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 head0.019
GPT teacher head0.306
Teacher spread0.287 · 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 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
Published2025
Admission routes3
Has abstractyes

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