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Record W3082017038 · doi:10.1016/j.ymgme.2020.08.007

Therapy development for the mucopolysaccharidoses: Updated consensus recommendations for neuropsychological endpoints

2020· article· en· W3082017038 on OpenAlexaff
Johanna H. van der Lee, J. Morton, Heather Adams, L. Clarke, Julie B. Eisengart, Maria L. Escolar, Roberto Giugliani, Paul Harmatz, Melissa Hogan, Shauna Kearney, Joseph Muenzer, Nicole Muschol, Stewart Rust, Benjamin R. Saville, Margaret Semrud‐Clikeman, Raymond Wang, Elsa Shapiro

Bibliographic record

VenueMolecular Genetics and Metabolism · 2020
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
FundersAllievexOrchard TherapeuticsAmicus TherapeuticsREGENXBIODenali TherapeuticsPTC TherapeuticsUltragenyx PharmaceuticalAeglea BioTherapeuticsSanofi GenzymeNational MPS Societybluebird bioShireAbeona TherapeuticsBioMarin Pharmaceutical
KeywordsNeuropsychologyMedicineClinical trialConsensus conferenceQuality of life (healthcare)CognitionNatural historyClinical PracticeIntensive care medicinePsychologyPsychiatryClinical psychologyPhysical therapyPsychotherapistPathology

Abstract

fetched live from OpenAlex

Neurological dysfunction represents a significant clinical component of many of the mucopolysaccharidoses (also known as MPS disorders). The accurate and consistent assessment of neuropsychological function is essential to gain a greater understanding of the precise natural history of these conditions and to design effective clinical trials to evaluate the impact of therapies on the brain. In 2017, an International MPS Consensus Panel published recommendations for best practice in the design and conduct of clinical studies investigating the effects of therapies on cognitive function and adaptive behavior in patients with neuronopathic mucopolysaccharidoses. Based on an International MPS Consensus Conference held in February 2020, this article provides updated consensus recommendations and expands the objectives to include approaches for assessing behavioral and social-emotional state, caregiver burden and quality of life in patients with all mucopolysaccharidoses.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.077
GPT teacher head0.346
Teacher spread0.269 · 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 designNot applicable
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

Citations37
Published2020
Admission routes1
Has abstractyes

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