Linking juvenile growth of white spruce with site index
Bibliographic record
Abstract
The goal of this study was to link the growth of juvenile white spruce stands with an estimate of their site index. We applied a previously developed technique for correcting the height bias created by dominance switching among juvenile trees before trees reached the site index base age (50 years at breast height), using stem analysis data of white spruce from five mixedwood stands in central Alberta. For white spruce of approximately 15 years total age, we found the height of the current top height trees was approximately 14% greater than the height of the top height trees that would be selected close to breast height age 50. This height correction is essential to avoid an overestimate of site index. Secondly, to avoid the difficulties of determining breast height age or growth increment required for juvenile site index determination, we developed a linkage to site index using data from 168 white spruce trees that were longitudinally sectioned along the pith, selected from juvenile (age 6–15) spruce stands. Using this new equation, coupled with the correction for bias, we found that site index for white spruce from 49 test stands in Alberta, ranged from 9.0 to 31.8 m at base age 50, with a mean of 17.8 m; these values are in the range for spruce in mixedwood stands in Alberta. Key words: juvenile stand, height age curve, height bias adjustment, site index
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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 | 0.000 | 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".