Early growth of white spruce underplanted beneath spaced and unspaced aspen stands in northeastern British Columbia
Bibliographic record
Abstract
We examined the growth of white spruce planted underneath a 33-year-old stand of trembling aspen following thinning and fertilization. Thinning the stand to 2000 stems·ha1 resulted in increased light reaching spruce seedlings and significant increases in height and diameter growth of seedlings over that observed in either the unspaced or 3000 stems·ha1 treatments. Fertilization (applied 3 years prior to planting) stimulated development of understory vegetation and did not benefit the planted spruce. While growth was improved by thinning, the benefits of the thinning treatment to establishment of white spruce appeared to be small, and amounted to increasing seedling height from 62 cm (unthinned) to 73 cm (thinned to 1000 or 2000 stems·ha1) at the end of 5 years. Results indicated that when stands are thinned for the purpose of accelerating growth rates of underplanted spruce, residual basal areas above 25 m2·ha1 should be retained to suppress growth of understory vegetation. Comparison of height at age 5 for seedlings planted under untended stands at Fort Nelson with three sites near Dawson Creek indicated no differences between locations, when height at the time of planting was included as a covariate.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".