Testosterone and estradiol concentrations in serum, velvet skin, and growing antler bone of male white-tailed deer
Bibliographic record
Abstract
The growth and mineralization of antlers correlate with the seasonal variation of serum androgens. Whereas seasonal levels of testosterone (T) in plasma are well established, steroid concentrations have not yet been determined in the tissues of growing antlers. Therefore, RIA was used to determine T and 17beta estradiol (E2) in serum, and three areas (tip, middle, and base) of the antler bone and the antler skin, called velvet. Blood and antler tissues of white-tailed deer (Odocoileus virginianus) were collected from May to August. The difference between levels of T and E2 among the sites was calculated using the square root transformation followed by a mixed model analysis with individual deer and an interaction of individual and year (individual(*)year) as a random factor. Concentrations of T in serum (799+/-82 pg/ml) were higher than T values in the velvet (589+/-58 pg/ml, P<0.01) and in the antler bone (538+/-58 pg/ml, P<0.001). Estradiol concentrations differed among antler tissues and serum (P<0.001) and between years (P<0.01). Estradiol concentrations in serum (25+/-25 pg/ml) were consistently lower than those in antler bone (208+/-11 pg/ml, P<0.001) and velvet (150+/-12 pg/ml, P<0.001). The E2:T ratio in serum was 1:10-60. The same ratio for the antler bone was only 1:2-3 and for the velvet 1:3.5. It is concluded that higher T and lower E2 concentrations found in plasma, as compared to antler bone or antler velvet, may indicate a partial metabolism of systemic androgens into estrogens xin the tissues of growing antlers.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".