Bibliographic record
Abstract
Sexual selection is the process of competing for access to a mate, and this includes intersexual selection and intrasexual selection. The two types of sexual selection include intrasexual and intrasexual selection, which is either the competition between members of the same sex or choosing a mate of the opposite sex, respectively. In intrasexual selection, weaponry is thought to be important as it increases competitive access. Recent research suggests that overall size and shape can be a predictor of fight outcome. Male Cyphoderris monstrosa are known to be aggressive when it comes to territory and mates, exhibiting this in contests. Using a vertical log arena, pairs of male Cyphoderris monstrosa were subjected to behavioural aggression trials. Contestants from the trials were dissected and photographs of their head, femora, and forewings were taken. Using these photographs, landmarks were used to determine morphological size and shape of each individual contestant. This study found that overall body size and measurements included in this analysis were not predictive of contest outcome. In addition to identifying the relationship between aggression and morphology in this species, this study provides evidence for the existence of two potential subspecies of C. monstrosa. Faculty Mentor: Kevin Judge Department: Biological Science
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 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) | 0.001 | 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".