Predicting the risk of wet ground areas in the Vanderhoof Forest District: Project description and progress report
Bibliographic record
Abstract
The mountain pine beetle epidemic is changing British Columbia forests and watersheds at the landscape scale. Watersheds with dead-pine-leading stands in the Vanderhoof Forest District of central British Columbia are reported to have wet soils due to raised water tables. They report a conversion of summer logging ground (dry firm soil) to winter logging ground (wetter less firm soil), upon which forestry equipment operation is difficult or impossible before freeze-up. This paper outlines a project that explores this serious operational issue through the perspective of the hydrologic water balance. It aims to determine the spatial extent of wet ground areas and to provide operational guidance through the development of a model that can predict where wet ground may occur at the stand and watershed level. The watershed-level prediction described here will be based on risk indicators developed from available geographic information system data and aerial photographs, as well as local knowledge. Predictions will be qualified through field verification studies at representative stands within ranked watersheds. Preliminary results are presented.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".