Females are the ecological sex: Sex‐specific body mass ecogeography in wild sifaka populations (<i>Propithecus</i>spp.)
Bibliographic record
Abstract
Previous work in primates has shown that body size often covaries with ecological parameters related to resource or energy availability in the environment. This relationship may differ for males and females as access to resources has greater importance for reproductive success in females. We test the hypotheses that (1) female body mass may be more tightly constrained than male body mass by ecological variables, and (2) female body mass may respond more strongly than male body mass to changes in ecological variables (i.e., population-specific female mass may vary more across an ecological gradient than male mass). Specifically, we investigate the relationship between climatic variables and sex-specific body mass in Propithecus, a genus in which species-specific body mass has already been demonstrated to covary significantly with climatic variables. Data from 733 wild sifakas are used to identify sex-specific body mass for 27 populations representing all nine described sifaka species, and climatic data for each population are derived from the WorldClim database. We use phylogenetic generalized least squares models to demonstrate that body mass in both sexes is significantly correlated with annual rainfall and number of dry months. Furthermore, coefficients of determination are always higher for female models, and coefficients for each climatic variable are higher for females in all significant models. These results support the two hypotheses tested, indicating that ecological forces can have a greater impact on female mass than on male mass in primates.
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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) | 0.002 | 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".