Meeting Report: Measuring Endocrine-Sensitive Endpoints within the First Years of Life
Bibliographic record
Abstract
An international workshop titled "Assessing Endocrine-Related Endpoints within the First Years of Life" was held 30 April-1 May 2007, in Ottawa, Ontario, Canada. Representatives from a number of pregnancy cohort studies in North America and Europe presented options for measuring various endocrine-sensitive endpoints in early life and discussed issues related to performing and using those measures. The workshop focused on measuring reproductive tract developmental endpoints [e.g., anogenital distance (AGD)], endocrine status, and infant anthropometry. To the extent possible, workshop participants strove to develop or recommend standardized measurements that would allow comparisons and pooling of data across studies. The recommended outcomes include thigh fat fold, breast size, vaginal cytology, AGD, location of the testis, testicular size, and growth of the penis, with most of the discussion focusing on the genital exam. Although a number of outcome measures recommended during the genital exam have been associated with exposure to endocrine-disrupting chemicals, little is known about how predictive these effects are of later reproductive health or other chronic health conditions.
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 | 0.014 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".