Importance of Vegetation for Identifying Wetlands in the Lower Mainland Fraser Valley region of British Columbia, Canada using Prevalence Index, Hydrophytic Cover Index, and Dominance Ratio
Bibliographic record
Abstract
The Lower Mainland Fraser Valley (LMFV) in British Columbia (BC), Canada is a complex and high stakes environment for wetland identification (Figure 1). High precipitation, subdued topography, and complex site history combine to present formidable challenges to wetland identification and management. Over the last 100+ years, the LMFV has undergone intense and rapid changes. Originally the land was a natural assortment of bogs, swamps and upland forests, which was then cleared for agriculture, and now is undergoing accelerating urban development. Land use competition is intense. Stakes are high: identification of wetlands can make or break development deals. Wetlands are protected in BC by the Water Sustainability Act, and administration is usually through municipal governments and bylaws. Jurisdictional wetlands are identified and mapped as part of a development permitting process.
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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 | 0.002 | 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 | 0.001 |
| 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 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".