A Watershed Level Economic Analysis of Cellulosic Biofuel Feedstock Production with Consideration of Water Quality
Bibliographic record
Abstract
<p>National policy supports the production of renewable energy from cellulosic feedstocks such as corn stover and switchgrass. These feedstocks have contrasting impacts on water quality. In this study, the regional supply response for cellulosic biofuel from these two feedstocks is estimated for the Le Sueur Watershed in South-Central Minnesota. The impacts of the resulting agricultural production activities on water quality in this northern corn belt watershed are also estimated. The Le Sueur River is a tributary of the Minnesota River, which in turn feeds into the Mississippi. The analysis is conducted with a multi-region, endogenous supply, mathematical programming model of the agriculture sector in the watershed. A unique aspect of the analysis is the spatial detail used in the production model. Results from a previous simulation analysis conducted with the Soil Water Assessment Tool (SWAT) model are used in the economic model to simulate the effects of the feedstock supply response on water quality in the Le Sueur. Sediment and nutrient losses from corn stover production make switchgrass more promising on environmental grounds, but the relatively high cost of production causes switchgrass to cover only a small part of crop land if farmers have unrestricted choice about how to supply cellulosic feedstocks.</p>
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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 | 0.001 |
| 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".