Sexual Dimorphism in Penguin Bill Length Across Species
Bibliographic record
Abstract
Sexual dimorphism, or biological differences between males and females of the same species, is a widespread phenomenon with important implications for ecology, evolution, and biodiversity (Tsuji, 2020). In birds, sexual dimorphism in bill morphology often reflects ecological specialization, sexual selection, or niche differentiation between sexes (Bolnick, 2003; Temeles, 2010). In penguins, bill morphology is a key functional trait linked to foraging ecology, mate choice, and species recognition, making it an ideal trait for studying dimorphism (Gorman, 2014). The availability of high-quality field data in the form of the palmerpenguins dataset (Horst, 2020) provides an opportunity to quantify sexual dimorphism in penguins and test whether its magnitude varies across different species. The palmerpenguins dataset provides standardized morphometric data for Adelie, Chinstrap, and Gentoo penguins in the Palmer Archipelago, allowing direct comparison of bill length across sexes and species. By testing whether bill length differs consistently between male and female penguins across species, this study contributes to a broader understanding of how sexual dimorphism presents across organisms and how it may relate to ecological differentiation. More specifically, it asks whether dimorphism is uniform across closely related species or whether species-specific ecological pressures (e.g., diet, habitat) influence its magnitude.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".