Identifying and preserving old-growth attributes in mixed forest stands dominated by yellow birch (Betula alleghaniensis) and balsam fir (Abies balsamea) in the context of ecosystem management in Québec
Bibliographic record
Abstract
The conservation of old-growth elements in managed forest is an important aim of the ecosystem management in Quebec. This work focus on their representation in yellow birch (Betula alleghaniensis) and balsam fir (Abies balsamea) stands of the mixed forest domain. We studied two experimental sites, one dominated by yellow birch and the other by balsam fir, where was estimated the effect of different forest treatments on oldgrowth characteristics. Our method shows the possibility to represent them with a small number of parameters, mainly dendrometric. Continuous cover treatments seems to be the most interesting systems for the conservation of these elements. However, our study raised the lack of information concerning old-growth stands in mixed forest. Yet, these data are essential for a relevant application of the ecosystem management. For this reason, further researches on this subject are necessary.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".