Coupe préparatoire et croissance en surface terrière d'une sapiniére de seconde venue à la forêt modèle du Bas-Saint-Laurent, Québec
Bibliographic record
Abstract
Balsam fir basal area growth was studied 5 years after the preparatory cut in the context of natural regeneration by the shelterwood system. The study was carried out in a 60-year-old second-growth balsam fir-yellow birch stand. The felling trials were realized in 16 plots and consisted of control and three felling regimes (15, 30 and 45% of removed basal area). The periodic (5 years) mean growth rate on dbh of trees in plots varies between 6 and 12% in response to felling intensity. The basal area of plots presents a mean periodic growth rate of 7.4% independently of felling intensity. There are highly significant correlations between the live crown characteristics and periodic basal area growth. This growth is highly correlated with inital diameter and intensity of felling. The trees of higher relative size are more productive than the others and the impact of felling on periodic basal area growth is significant when the intensity of felling is greater than 30%. Conversely, the ratio between periodic basal area growth after treatment and periodic basal area growth before treatment is correlated only with the intensity of felling. Finally, intensity of felling had no effect on periodic basal area growth per square meter of crown projected area. Key words: preparatory felling, basal area growth, balsam fir
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.004 | 0.001 |
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".