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Record W7116783849 · doi:10.1002/mds.70163

Transforming Pediatric Movement Disorders Assessment: From Expert Consensus to Collaborative Approaches

2025· article· en· W7116783849 on OpenAlexafffund
Hortensia Gimeno, Clément Desjardins, C. Nilles, Kathryn Peall, Tamara Pringsheim, E. Roze

Bibliographic record

VenueMovement Disorders · 2025
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersDystonia Medical Research Foundation CanadaCanadian Institutes of Health ResearchParkinson CanadaDepartment of Health and Social CareFondation pour la Recherche MédicaleUniversity of OxfordUniversity of CalgaryTourette Association of AmericaAgence Nationale de la RechercheMedical Research CouncilInternational Parkinson and Movement Disorder SocietyAmadysAlberta Health ServicesMerz PharmaceuticalsNational Institute for Health and Care ResearchTeva Pharmaceutical Industries
KeywordsMEDLINEMovement disordersMovement (music)Patient privacyData sharing

Abstract

fetched live from OpenAlex

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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)0.436
metaresearch head score (Gemma)0.499
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.436
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4360.499
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0150.007
Science and technology studies0.0050.006
Scholarly communication0.0120.012
Open science0.0100.034
Research integrity0.0040.011
Insufficient payload (model declined to judge)0.0060.004

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 head0.285
Teacher spread0.266 · 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.

Study designTheoretical or conceptual
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 routes2
Has abstractyes

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