ANTLER SIZE RELATIVE TO BODY MASS IN MOOSE: TRADEOFFS ASSOCIATED WITH REPRODUCTION
Bibliographic record
Abstract
Body size and age are highly correlated with antler size, fighting ability, and reproductive success in male cervids. Production of antlers requires energy above that for maintenance ofbasal functions, and is especially demanding of minerals. In addition to producing antlers, young cervids also incur the cost of completing body growth. Large-bodied males with large antlers invest more in antler development and reproduction at the expense of body condition than do young males. Young males are constrained by the need to complete body growth to attain the body size necessary to compete effectively for females when mature and, hence, invest less in antlers . We tested the hypothesis that adult male moose (A/ces alces) produced larger antlers relative to their body mass than did younger males. We used regression to compare the ratio of antler length per unit body mass (antler length: body mass) with age. Regression analysis indicated a strong curvilinear relationship (R. 2 = 0.961) between antler length per unit body mass and age. Young males invested less in antlers than older males that had reached a sufficient size to compete effectively for mates; consequently, there was a tradeoff between body growth and antler size. Young males must produce antlers to gain experience in aggressive encounters and establish dominance relationships among their cohort, although investment in antlers is less than that of mature adults. Delaying investment in mating until physically mature and able to compete for females with other large-antlered males is the most successful strategy for maximizing mating success and achieving the greatest fitness in male moose, as well as among other cervids. ALCES VOL. 36: 77-83 (2000)
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".