Urinary Sex Steroids during Sexual Development in Female Mice and in Proximate Novel Males
Bibliographic record
Abstract
The experiments described here were designed to determine whether males' capacity to accelerate female pubertal development is reflected in females' urinary steroid levels in mice, and whether steroids in males' urine are influenced by exposure to developing females. In the first experiment, measures from urine collected daily from female mice aged 31-59 days showed a gradual rise in 17beta-estradiol levels and a distinct linear rise in progesterone levels. In a second experiment, daily steroids were measured in females aged 30-42 days while they were either housed alone or underneath two novel outbred males. Females exposed to males showed accelerated development at day 43 in uterine weight, and to a lesser extent in ovarian and whole-body weights. Average steroid levels did not significantly differ between conditions, but intra-individual variance in estradiol measures was greater in male-exposed than in isolated females. Creatinine levels were higher in isolated females. Males exposed to developing females excreted higher levels of estradiol in their urine compared to isolated males. These data suggest that excreted steroids can reflect general pubertal development, but may not fully reflect substantial morphological impacts of exposure to novel males. Elevations of estrogen levels in males exposed to developing females could help to account for precocious puberty in such females.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".