One size does not fit all: Toward regional conservation practice guidance to reduce phosphorus loss risk in the Lake Erie watershed
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
Agricultural phosphorus (P) losses to surface water bodies remain a global eutrophication concern, despite the application of conservation practices on farm fields. Although it is generally agreed upon that the use of multiple conservation practices ("stacking") will lead to greater improvements to water quality, this may not be cost effective to farmers, reducing the likelihood of adoption. At present, wholesale recommendations of conservation practices are given; however, the application of specific conservation practices in certain environments (e.g., no-till with surface application, cover crops) may not be effective and can even lead to unintended consequences. In this paper, we present the Lake Erie watershed as a case study. The Lake Erie watershed contains regions with unique physical geographies that include differences in climate, soil, topography, and land use, which have implications for both P transport from agricultural fields and the efficacy of conservation practices in mitigating P losses. We define major regions within the Lake Erie watershed where common strategies for conservation practice implementation are appropriate, and we propose a five-step plan for bringing regionally tailored, adaptive, and cost-conscious conservation practice into watershed planning. Although this paper is specific to the Lake Erie watershed, our framework can be transferred across broader geographic regions to provide guidance for watershed planning.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 it