Do Closely Related Species Influence Each Other's Sexual Size Dimorphism?
Bibliographic record
Abstract
Size differences between males and females (sexual size dimorphism) are often seen in a variety of species. In birds of prey in particular, a phenomenon occurs where the female is larger than the male. One of the main hypotheses attempting to explain sexual size dimorphism in birds of prey is that the female and male differ in size to partition resources, like prey. There is also evidence that predator and prey body size are correlated, so predators of similar size may be in direct competition. It has been shown that when two closely related species interact in the same area, they are likely to be in competition for similar resources, like prey. This study is looking at sexual size dimorphism and closely related species interactions, which has never been looked at before in birds of prey. I am using the subfamily Buteoninae (Buteo Hawks) as my focal group. I will be using sexual size dimorphism ratios, estimates of genetic distance between closely related species and proportion of range overlap between different closely related lineages within the subfamily. I am expecting to see that if species are closely related and inhabit the same area they will have a decreased sexual size dimorphism. This is because both species are likely to be competing for the same resources, and to avoid competition the species will diverge in body size from one another. This will cause the male and female of each species to converge in size, reducing their sexual size dimorphism.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".