Growth, allometry, and characteristics of a sexually selected structure in wolverine (<i>Gulo gulo</i> (Linnaeus, 1758)), northern river otter (<i>Lontra canadensis</i> (Linnaeus, 1758)), and sea otter (<i>Enhydra lutris</i> (Linnaeus, 1758))
Bibliographic record
Abstract
Allometric analyses of sexually selected structures have revealed many patterns of evolutionary and behavioural significance, for example, in weapons, ornaments, and genitalia. We investigated allometry of the baculum (penis bone) relative to body size in post-growth adults of three large mustelids: wolverine ( Gulo gulo (Linnaeus, 1758)), northern river otter ( Lontra canadensis (Linnaeus, 1758)), and sea otter ( Enhydra lutris (Linnaeus, 1758)). The baculum grew over a longer period than did body size. Correlations among bacular variables were positive in post-growth adults. No regression slopes expressed positive allometry (i.e., slope > 1 for linear variables). These trends point to the possibility that bacular size is adapted to the average size of the reproductive tract of sexually mature female northern river otters and possibly sea otters, and that pre-ejaculatory (“pre-copulatory”) selection is highest in those species. Bacular size varied more than skull or limb-bone size, and bacular shape also varied greatly. Species differed in size and complexity of the urethral groove and bacular apex, suggesting functional differences in intromission. Substantial variation in bacular shape resulted from healed fractures, especially in sea otter. Knowledge of copulatory behaviour, age of breeding, female reproductive anatomy, and genitalic interactions during intromission is needed for comprehensive understanding of bacular anatomy, allometry, and variation for these species.
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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 | 0.000 | 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".