Bibliographic record
Abstract
Sexual dimorphism refers to differences in size and shape between females and males of the same species. The term sexual dimorphism is usually used only for the secondary sexual characteristics, which are unrelated to reproduction. Some examples of sexual dimorphism include differences in stature, weight, morphology of the face, cognitive development, mortality, and disease prevalence. Although humans exhibit low levels of sexual dimorphism compared to other animals, differences between females and males are numerous. Evolutionary, sexually dimorphic traits develop through the process of sexual selection. Furthermore, mating system, body size, gender roles, and quality of environment also play an important role in determining the levels of sexual dimorphism. Sexual dimorphism has an important place in biological anthropology. In bioarchaeology and forensic anthropology, morphological and metric traits are used to estimate sex of the skeletal remains, while in studies of human evolution the level of sexual dimorphism is used to reconstruct social behavior. Generally, the majority of studies tend to focus on adults, because sexual dimorphism is not well pronounced before puberty.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.006 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.447 | 0.008 |
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; both teacher heads agree on what is shown here.
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".