Effects of stand tending on the estimation of aboveground biomass of planted juvenile white spruce
Bibliographic record
Abstract
Stem, branch, needle, and total aboveground biomass were assessed for three 9- to 12-year-old white spruce (Picea glauca (Moench) Voss) plantations, each subjected to three different stand tending options at age 4 to 7. Biomass components were predicted from measures of stem diameter with coefficients of variation between 24% and 29%. Diameter at breast height (DBH) generally provided lower prediction precision than did the lower stem measures tested (coefficient of variation > 35%). The addition of tree height in models reduced the standard error of the estimates for stem and total biomass by an average of 48% and 8%, respectively, and compensated for different height/diameter ratios imposed on the spruce by the stand tending treatments. Needle and branch biomass models were invariant to the tending treatments and, consequently, to the addition of height as an independent variable. Predictions from existing published white spruce equations suggest that extrapolation to this study area would have led to adequate stem biomass estimation but to serious (>55%) underestimates of branch, needle, and, correspondingly, total biomass. Slow self-pruning by plantation spruce, particularly before crown closure, is cited as a possible reason for these differences.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".