Bibliographic record
Abstract
OBJECTIVES: To provide a summary of the recent major advances in the field of molecular genetics and understanding of psychosexual development, as these developments have resulted in changes in terminology and classification of disorders of sexual differentiation (DSD)/intersex; and to provide a quick and simplified review of the basic information. METHODS: Recent publications (over the last 10 years) were identified by a PubMed search, as were relevant previous studies, using the keywords; 'sex chromosomes', 'psychosexual development', 'classifications', 'disorders of sexual differentiation', 'Chicago consensus', 'gonadal malignancy', 'intersex' and 'ambiguous genitalia'. RESULTS: The newly proposed terminology and classification has eliminated some confusion for both patient and family, as well as among health professionals. The new advances have facilitated the categorisation of gonadal malignancy in patients with DSD into high-, intermediate- and low-risk groups. CONCLUSIONS: The major changes in terminology and classification of DSD should be considered as the first steps on a long road of research effort. The current available data remain far from sufficient. More molecular genetics studies will allow a better understanding of the causes of each condition of DSD.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".