Datasets of productivity and vegetation composition of boreal stands from an experiment comparing silviculture scenarios of increasing intensity after 20 years
Bibliographic record
Abstract
This data article describes datasets of plant community composition, dendrometric measurements, quantity and quality of snags of humid boreal stands (Quebec, Canada) from an experiment comparing silviculture scenarios of increasing intensity: (i) careful logging around advance growth (CLAAG); (ii) CLAAG followed by pre-commercial thinning; (iii) plantation followed by mechanical release; and (iv) plantation followed by chemical release and within five naturally disturbed sites. These data enable researchers to examine vegetation biodiversity recovery, ecosystem variables such as dead wood, and boreal stand productivity 20 years following the start of increasing-intensity silviculture scenarios. As a result, these data can be used to investigate the trade-off between keeping important ecosystem aspects of natural forests and maintaining and/or growing merchantable wood production at the stand level. This trade-off is the paradigm of forest ecosystem-based management, which aims to reduce the ecological distance between natural and managed forests in order to balance ecological challenges with the provision of socioeconomic services.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".