The androgen receptor gene mutations database (ARDB): 2004 update
Bibliographic record
Abstract
The current version of the androgen receptor (AR) gene mutations database is described. The total number of reported mutations has risen from 374 to 605, and the number of AR-interacting proteins described has increased from 23 to 70, both over the past 3 years. A 3D model of the AR ligand-binding domain (AR LBD) has been added to give a better understanding of gene structure-function relationships. In addition, silent mutations have now been reported in both androgen insensitivity syndrome (AIS) and prostate cancer (CaP) cases. The database also now incorporates information on the exon 1 CAG repeat expansion disease, spinobulbar muscular atrophy (SBMA), as well as CAG repeat length variations associated with risk for female breast, uterine endometrial, colorectal, and prostate cancer, as well as for male infertility. The possible implications of somatic mutations, as opposed to germline mutations, in the development of future locus-specific mutation databases (LSDBs) is discussed. The database is available on the Internet (http://www.mcgill.ca/androgendb/).
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.020 |
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".