Bibliographic record
Abstract
Text: The Maumee Basin Watershed encompasses Ohio, Michigan and Indiana which drains to Lake Erie, the most biologically productive of the Great Lakes. The Western Lake Erie Basin (WLEB) Partnership began in 2005 with collaborations between USDA Natural Resources Conservation Service (NRCS) and the U.S. Army Corps of Engineers (USACE) with the signing of a partnership agreement. The agreement states the two agencies will collaborate on watershed planning and implementation; wetland creation, restoration, and enhancement; and natural disaster recovery. In Ohio, the NRCS and USACE signed a regional agreement supporting the activities outlined in the national agreement, focusing on the Western Lake Erie Basin. In March 2006, a WLEB Partnership charter was signed by fourteen agencies and organizations and partnership bylaws were adopted. NRCS roles and responsibilities include performing rapid assessments for each 8-digit sub-watershed of the Maumee Basin Watershed to identify current resource conditions on private lands, recommend systems to solve identified problems, and estimate (quantitative and/or qualitative) on-farm effects. Farm Bill land treatments have also been implemented in collaboration with Environmental Defense, Ohio Farm Bureau Federation, the Conservation Action Project, and Soil and Water Conservation Districts, including special farmer-focused initiatives under Environmental Quality Incentives Program to improve water quality in the WLEB. Farmers in the St. Mary, Tiffin, Grand Lake St. Mary, and Blanchard River Watersheds can participate. USACE roles and responsibilities include a comprehensive WLEB Study to investigate measures to improve fish and wildlife habitat, navigation, flood damage reduction, recreation, and water quality in the Maumee, Ottawa and Portage River watersheds. Continuing Authorities Projects (CAP's) will allow for the planning, design and construction of relatively small projects. The CAP programs have two phases: feasibility, and design and implementation. This poster identifies Water Quality accomplishments in the Western Lake Erie Basin through NRCS, USACE and the WLEB Partnership efforts. Impact Statement: With the development of NRCS' Rapid Assessment tool, USACE Comprehensive WLEB study, and collaborating partners, the WLEB Partnership is improving water quality utilizing communities and watershed groups in eight sub-watersheds in the Western Lake Erie Basin. In collaboration with NRCS, USACE, Environmental Defense, and other partners, improvements include a data profile that contains various maps and GIS layers with explanatory text and tables including digital elevation, land cover, land use trends, riparian zone analysis, soils information, agricultural statistics, conservation practice improvements, local watershed group activities, and various other sets of water resource data. For additional information, visit www.wleb.org
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.220 | 0.107 |
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".