Target Ecosystem Assessment Model: a process to develop target revegetation prescriptions in the mine closure landscape
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
The Target Ecosystem Assessment Model (TEAM) was developed to provide mine reclamation practitioners with an iterative process to refine final closure reclamation plans. Using the ArcGIS™ platform, it incorporates inputs from multiple sources including soil cover design; topography; hydrology and wetlands; soil nutrient regime and stakeholder inputs to develop revegetation prescriptions for target ecosystems. The model output is used to guide vegetation prescription suitability with an appropriate predicted relative moisture (driest to wettest) regime. To develop the TEAM, various input layers are overlaid sequentially to create unique relative estimated moisture regime areas. Slope position and soil texture are influential factors of moisture regime in areas not directly influenced by the water table. In transitional areas and wetland areas, topographic position and proximity to water and/or water table are more influential to moisture regime predictions. With this information, a range of suitable target revegetation prescriptions can be generated from estimated relative moisture regime derived from the model and nutrient regime derived from the soil cover characteristics (i.e. the soil prescription). The output of the model provides planners with a range of moisture classes tied to specific ecosystems, and the soil and vegetation prescriptions that support them. The TEAM reduces the potential subjectivity of planning by matching ecosystem target options to each unique combination of site conditions, and in doing so, testing for mismatches in site conditions and desired end land uses. The TEAM provides flexibility in creating the target ecosystem layouts, by including stakeholder input for desired end land use and consideration of the complexity and arrangement of ecosystems in the pre-disturbance landscape. This information is used to further delineate areas for specific revegetation prescriptions (targeted vegetation community assemblages). Planners who use the TEAM can be confident in defensible target ecosystem layouts, which are developed using a standard, tested procedure.
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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 | 0.001 | 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) | 0.001 | 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