Wildlife/danger tree assessment in unharvested stands attacked by mountain pine beetle in the central interior of British Columbia
Bibliographic record
Abstract
This extension note outlines work that was part of a broader study designed to collect baseline forest structure data in the Sub-Boreal Spruce dry cool biogeoclimatic subzone (SBSdk) of the Lakes Timber Supply Area (TSA). This data will help to assess the future ecological impacts of the mountain pine beetle. A primary component of our research was to determine the safest possible work or recreation window for individuals planning entry into stands killed by the mountain pine beetle. The provincial Wildlife/Danger Tree Assessment criteria were used to determine the types and frequency of danger trees in these stands. Data collected included species, height, diameter at breast height, and the presence or absence of danger tree characteristics for each mature tree. The majority of the trees in this study were classified as either class 1 (alive and healthy) or class 3 (recently dead). One mountain-pine-beetle-killed tree had fallen. Approximately 85 stems per hectare, or 5.5% of all trees, had a defect considered potentially dangerous. Most defects were found in the smaller diameter classes. The study area was significantly affected by mountain pine beetle; areas of high use (e.g., recreation-, cultural-, or work-related) may require specific mitigation activities to ensure user safety.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".