Bibliographic record
Abstract
Pediatric endocrinologists often evaluate and treat youth with delayed puberty. Stereotypically, these patients are 14-year-old young men who present due to lack of pubertal development. Concerns about stature are often present, arising from gradual shifts to lower height percentiles on the population-based, cross-sectional curves. Fathers and/or mothers may have also experienced later than average pubertal onset. In this review, we will discuss a practical clinical approach to the evaluation and management of youth with delayed puberty, including the differential diagnosis and key aspects of evaluation and management informed by recent review of the existing literature. We will also discuss scenarios that pose additional clinical challenges, including: (1) the young woman whose case poses questions regarding how presentation and approach differs for females vs males; (2) the 14-year-old female or 16-year-old young man who highlight the need to reconsider the most likely diagnoses, including whether idiopathic delayed puberty can still be considered constitutional delay of growth and puberty at such late ages; and finally (3) the 12- to 13-year-old whose presentation raises questions about whether age cutoffs for the diagnosis and treatment of delayed puberty should be adjusted downward to coincide with the earlier onset of puberty in the general population.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".