Bibliographic record
Abstract
Rett syndrome (RTT) was first recognized in the late 1950s by Andreas Rett in Vienna and Bengt Hagberg in Uppsala. Hagberg, following a meeting with Rett, decided to call the disorder Rett syndrome in the landmark paper which appeared in the Annals of Neurology in 1983. That report led to the worldwide recognition of this relatively young and unique neurodevelopmental disorder, the concerted effort to establish its epidemiology, etiology, and natural history, and the establishment of clinical criteria for its diagnosis. Our understanding of RTT progressed rapidly, in part due to the remarkable diagnostic advances in genetics linking RTT with variations in the methyl-CpG-binding protein 2 (MECP2) gene at Xq28. In 2003, the NIH funded a Natural History study of RTT and related disorders which provided critical cross-sectional and longitudinal data that resulted in the increased understanding of RTT, the development of better management strategies, and an increase in pharmaceutical and gene-based products designed to provide specific therapies. The FDA-approved oral agent trofinetide has been shown to provide incremental improvements in the core features of RTT. Two gene-based therapies are currently being assessed in clinical trials in Canada and the US. Additional treatment strategies are being assessed at the clinical and translational levels.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".