Physical properties of dead and downed round-wood fuels in the Boreal forests of western and Northern Canada
Bibliographic record
Abstract
The quantity of dead and downed woody fuels in forests is commonly estimated using the line intersect method of sampling. Determination of the mass of wood per unit area for each size class requires values for the mean specific gravity, piece tilt angle and piece diameter. We present these values for dead and downed round-wood materials less than 7 cm in diameter based on surveys of slash and naturally fallen materials in six boreal forest regions of western and northern Canada and for eight common species in these regions. There was considerable variation in the three variables: mean specific gravity ranged from 0.34 to 0.65 Mg m–3, tilt ranged from 5° to 33°, and mean squared diameter ranged from 31% below to 71% above the value at class mid-point. Values of each were strongly related to size class, species, fuel type and to region. We conclude that values derived from other study areas or species can give substantial inaccuracies in estimating dead and downed round-wood fuel loads if applied to sites within the study region, although ultimate accuracy obtainable will be more influenced by the length of sampling line. The three variables are combined into a single factor so that fuel loads can be simply calculated by multiplying this factor by the number of intersects per metre of transect.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".