Therapy development for the mucopolysaccharidoses: Updated consensus recommendations for neuropsychological endpoints
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.062 | 0.115 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.009 | 0.006 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".