Ejaculate investment in a promiscuous rodent, Peromyscus maniculatus: effects of population density and social role
Bibliographic record
Abstract
Questions: How does average male investment in ejaculates vary with changing population density (and thus with the risk of sperm competition) in a promiscuous species? Do individual male investment strategies vary with population density? Data studied: Total testicular mass, somatic mass and annual population density for wild-caught male deer mice, Peromyscus maniculatus, collected by snap-trapping over a 23-year period in Algonquin Provincial Park, Ontario, Canada. Search methods: We analysed the relation between mean testicular mass and mouse population densities across years. To investigate individual investment patterns, we compared the relation between total testicular mass and somatic mass among males for years differing in population density. Conclusions: Average investment in the testes was positively correlated with annual population density. An individual’s investment in testes depended on both the abundance of rival males and on relative body size, a trait associated with social rank.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".