Mitigating infrastructure loss from beaver flooding: A cost–benefit analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We installed 12 pond levelers to counter flooding by beavers and developed a cost–benefit analysis for these sites in Alberta, Canada. We also documented beaver management approaches throughout Alberta. Over 3 years, one site required regular maintenance until we designed a modified pond leveler; another required minor modifications. Others required almost no maintenance. Based on a “willingness-to-pay” (WTP) of $0 and discount rate of 3%, installing pond levelers resulted in a present value net benefit of $81,519 over 3 years and $179,440 over 7 years. Scenarios incorporating discount rates of 3% and 7%, horizons of either 3 or 7 years, and varying WTPs resulted in significant net benefits. Provincially, municipalities employed up to seven methods to control beavers: most commonly lethal control and dam removal. Total annual costs provided by 48 municipalities and 4 provincial parks districts were $3,139,223; however, cost-accounting was sometimes incomplete, which makes this a conservative estimate.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it