Swimming Wolves, <em>Canis lupus</em>, Attack a Swimming Moose, <em>Alces alces</em>
Bibliographic record
Abstract
In August 2008 at a small pond on Isle Royale, Michigan, we saw three Wolves (Canis lupus) run towards and leap at or onto a cow Moose (Alces alces) standing at the shore's edge in water ca. 1.7 m deep. The Moose swam out into the pond with the Wolves swimming in pursuit while attempting, with occasional success, to climb on the back of the Moose. The chase eventually moved out of our view, but a week later we found a Wolf-eaten cow on the pond's shoreline where we estimated it might have been killed. The animal was ca. 14-yr old with arthritic lesions in the pelvic region. This is apparently the first published report of swimming Wolves attacking and killing a swimming Moose, the kill likely having been made as the Moose emerged from the pond. Remains of a second kill in that pond were found shortly thereafter.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".