Étude des facteurs associés au dépérissement du bouleau à papier en peuplement résiduel après coupe
Bibliographic record
Abstract
Following harvesting operations within the Quebec mixedwood region, decadence symptoms are frequently observed on residual paper birch trees, compromising future harvests. Simultaneously, these residual stands are often a constraint to the establishment and growth of valuable regeneration. In the context of intensive forest management and preservation of the conifer component in mixedwood stands, it is important to identify factors associated with paper birch post-logging decadence. Ninety-eight (98) stands were sampled along a partial cutting chronosequence of 1 to 11 years old in order to examine five site variables and six stand variables susceptible of explaining post-logging decadence. Classification and regression tree (CART) models indicated that stand variables, mainly residual basal area and time since harvest, were the best predictor variables of decadence. This study suggests maintaining a basal area of at least 16 m2/ha and preserving larger diameter stems when the objective is to maintain healthy paper birch for further harvesting. When the silvicultural objective is to regenerate softwoods, this study recommends keeping a residual basal area after partial cutting of no more than 4 m2/ha. Keywords: residual trees, competition, mixed stands, partial cutting, tree regression, regeneration
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".