Site-Index Curves and Growth Intercepts for Young White Spruce Plantations in North Central Ontario
Bibliographic record
Abstract
Abstract Site-index (heightߝgrowth) curves, site-index prediction equations, and growth intercepts were developed from internode measurements and stem-analysis data using dominant trees in 69 plots located in white spruce plantations aged 19 to 32 years total age. Site-index curves were based on breast-height (1.3 m) age because our analyses show that height growth below breast height is slow and erratic and is poorly related to site index (dominant height at 15 years breast-height age). The most precise model for computing heightߝgrowth curves was a Newnham constrained polymorphic expression (Newnham, R.M. 1988. A modification of the Ek-Payandeh nonlinear regression model for site-index curves. Can. J. For. Res. 18:115ߝ120) of the Ek nonlinear regression model (Ek, A.R. 1971. A formula for white spruce site-index curves. University of Wisconsin For. Res. Note 161. 2 p). Comparisons showed that site-index curves in North Central Ontario were comparable to site-index curves for white spruce plantations in southeastern Ontario. The first three to five internodes above 2.0 m gave the most precise estimates of site index based on growth intercepts. North. J. Appl. For. 23(4):257–263.
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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 | 0.000 | 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) | 0.001 | 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".