Evaluation of alternative management strategies of muskrat Ondatra zibethicus population control using a population model
Bibliographic record
Abstract
Abstract Muskrats Ondatra zibethicus are considered a pest species in the Netherlands, and a year‐round control programme is in effect. Currently, the agency responsible for the management of muskrat populations in the Netherlands (the LCCM) is preparing for field studies to compare alternative strategies of control. In order to decide on the specific design of such field studies, a population dynamic model was built. The model compares the current management strategy with alternatives in which the effort is focused in space or in time. The model allows us to prioritise future research questions. The major gaps in knowledge at this moment are: 1) insight into the costs of harvesting at different harvest rates, and 2) the relationship between population density on the one hand and (financial damage or) safety risk on the other hand. We suggest continuing the current management, and to test our hypothesis that intensifying harvest will lead to lower numbers of animals killed in the medium term than more extensive harvest rates. The muskrat control programme offers excellent opportunities for applied biological studies of which the benefits are likely to outweigh the costs.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".