Review of deer ked (Lipoptena cervi) on moose in Scandinavia with implications for North America.
Bibliographic record
Abstract
The deer ked (Lipoptena cervi) is an Old World dipteran ectoparasite of moose (Alces alces) and other Cervidae. It has undergone significant expansion in distribution on moose of Scandinavia in recent decades. This has been accompanied by much published research dealing with the range expansion and possible factors involved, problems for moose, exposure of northern populations of reindeer (Rangifer rangifer tarandus), and public health issues. Apparently, Lipoptena cervi was introduced into northeastern United States in the late 1800s, presumably on an unknown species of European deer, and it soon spread to white-tailed deer (Odocoileus virginianus). We review the current situation in Scandinavia and North America and document the first record of L. cervi on moose in northeastern United States.
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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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".