The Canadian Neuromuscular Disease Registry 2010–2019: A Decade of Facilitating Clinical Research Througha Nationwide, Pan-NeuromuscularDisease Registry
Bibliographic record
Abstract
We report the recruitment activities and outcomes of a multi-disease neuromuscular patient registry in Canada. The Canadian Neuromuscular Disease Registry (CNDR) registers individuals across Canada with a confirmed diagnosis of a neuromuscular disease. Diagnosis and contact information are collected across all diseases and detailed prospective data is collected for 5 specific diseases: Amyotrophic Lateral Sclerosis (ALS), Duchenne Muscular Dystrophy (DMD), Myotonic Dystrophy (DM), Limb Girdle Muscular Dystrophy (LGMD), and Spinal Muscular Atrophy (SMA). Since 2010, the CNDR has registered 4306 patients (1154 pediatric and 3148 adult) with 91 different neuromuscular diagnoses and has facilitated 125 projects (73 academic, 3 not-for-profit, 3 government, and 46 commercial) using registry data. In conclusion, the CNDR is an effective and productive pan-neuromuscular registry that has successfully facilitated a substantial number of studies over the past 10 years.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".