PHENOTYPIC VARIATION IN MOOSE: THE ISLAND RULE AND THE MOOSE OF ISLE ROYALE
Bibliographic record
Abstract
There is strong empirical support for the island rule, whereby body size in insular popula- tions of animals tends toward gigantism in small-bodied species and dwarfism in large-bodied species (>10 kg). For large-bodied species, underlying reasons for dwarfism in insular populations include lack of predation and resource limitation. We found that metatarsal length of moose (Alces alces) from Isle Royale National Park in Lake Superior (North America) was significantly shorter than that of mainland moose in Minnesota and Michigan. On Isle Royale, moose body size was inversely related to moose density at the time of birth, illustrating the resource limitation that is influential where average moose density is 5-10 times higher than on the mainland. Reduced body size probably developed in Isle Royale moose within a half century of their establishment, prior to the arrival of wolves (Canis lupus), and subsequently body size should be shaped by the countervailing influences of resource limitation and predation by wolves. Bones provide an excellent basis for spatio-temporal comparisons of body size among moose populations. With additional data on metatarsus length from moose in Alaska and Sweden, we illustrate important considerations such as sample size, sex differences, and biases arising from source of bone collections. ALCES VOL. 47: 125-133 (2011)
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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 | 0.002 |
| 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 | 0.001 | 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".