Community‐Sourced Reporting of Mortalities in Angelman Syndrome (1979–2022)
Bibliographic record
Abstract
Angelman syndrome (AS) is a severe genetic neurodevelopmental disorder with an estimated prevalence of 1:20,000. Life expectancy appears to be normal, however, data regarding lifespan in AS are scarce. Until 2018, there was no unique diagnosis code for AS, thus true incidence, prevalence, mortality and morbidity rates are unknown. A social media effort was launched by caregivers of people with AS to gather community-sourced data to understand AS mortality risks. Information on 220 deaths was verified with obituaries and public postings. Respiratory illness was the primary cause of death among people with AS overall, followed by accidents and seizures. Surprisingly, sudden unexpected death in sleep (SUDS) was the fourth most common cause, which has not been reported previously. Approximately 91% of people with AS have epilepsy, thus some SUDS cases may represent sudden unexpected deaths in epilepsy (SUDEP). Causes of death vary by age, and differ from the general population. Though there are obvious limitations to data collected through social media, grass roots science is a starting point to amass preliminary data and inform future epidemiological research on AS.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".