Taper Equations for Five Major Commercial Tree Species in Manitoba, Canada
Bibliographic record
Abstract
Abstract Kozak's variable exponent taper equation was fitted for balsam poplar (Populus balsamifera L.), trembling aspen (Populus tremuloides Michx.), white spruce (Picea glauca [Moench] Voss), black spruce (Picea mariana [Mill.] B.S.P.), and jack pine (Pinus banksiana Lamb.) in Manitoba. Stem taper variability between two ecozones (i.e., Boreal Shield and Boreal Plains) were tested using the F-test. Regional differences were observed for trembling aspen, white spruce, and jack pine, and for those species, separate ecozone-specific taper equations were developed. However, the gross total volume estimates using the ecozone-specific equations were different from those of the provincial equations by only 2 percent. Although the regional difference in stem form was marginal within a province, a difference of approximately 7 percent of gross total volume estimation was found when our provincial taper equations were compared with those developed in Alberta and Saskatchewan. These results suggest that stem form variation increases with spatial scale and that a single taper equation for each species may be sufficient for each province.
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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 | 0.001 | 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) | 0.002 | 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".