RettBASE: The IRSA MECP2 variation database—a new mutation database in evolution
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rett syndrome (RTT) is a neurodevelopmental disorder affecting primarily females, with an incidence of around 1 in 15,000 females. In 1999, mutations in the X-linked gene methyl-CpG-binding protein 2 (MECP2) were first reported in RTT subjects, and since that time there have been a number of publications describing cohorts of patients and their mutations. In addition, MECP2 mutations have been reported in patients who do not fit the diagnostic criteria for Rett syndrome. We have developed a new locus-specific database, RettBASE (http://mecp2.chw.edu.au/), loosely based on the PAHdb website. The aim is to obtain data relating to all known instances of MECP2 variations, including published ta and data directly submitted by one of various means (either by using an online submission form, or by sending the same form in Adobe portable document format (pdf) or Microsoft Word format by email or fax to the database curators). The database has a range of query capabilities, allowing for simple or complex interrogation of the database. To address the issue of patient confidentiality, we have incorporated an Excel spreadsheet algorithm that allows the generation of a unique number based on the subject's name and date of birth. We believe this database will prove to be a useful resource, allowing the development of accurate prevalence data for disease-causing mutations, providing a catalog of polymorphisms, and potentially allowing more accurate phenotype-genotype correlations to be drawn.
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.
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 it