Spatial Patterns of Sexual Dimorphism in Minks (Mustela vison)
Bibliographic record
Abstract
Spatial patterns of sexual dimorphism in minks (Mustela vison) from 35 localities in North America were examined using 25 cranial characters to test predictions of the resource partitioning hypothesis of sexual dimorphism. Specific hypotheses evaluated were that trophic structures would be among the most dimorphic and would not be strongly correlated to body size characters. Twenty of 25 characters were significantly larger in males. Predictions of the resource partitioning hypothesis were not supported as canine diameter, a widely used indicator of resource partitioning, was not sexually dimorphic and there was a relatively large correlation between body size traits and trophic traits. Significant spatial variation in degree of dimorphism was found. The patterns of sexual dimorphism from principal components analysis indicated that largest degrees of sexual dimorphism were found in minks from Pennsylvania and Florida and least degrees of dimorphism were in minks from Alaska and Quebec. Sexual dimorphism may have an important temporal component which should be investigated in further studies.
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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 | 0.001 |
| 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 | 0.000 |
| 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".