Bibliographic record
Abstract
Driven by issues of economics, productivity, biodiversity and climate change, mixedwood management is becoming increasingly attractive. For silviculture to embrace and capitalize on natural stand dynamics, complex processes and interactions must be understood. To facilitate focused, applied research, ten Alberta forest companies have joined forces to cooperatively advance the science and management of boreal aspen/white spruce mixedwood forests. Members of the Mixedwood Management Association have committed collective research funds to develop and test practices that will sustain fibre supply, biodiversity, social and ecological values in Alberta's mixedwood forests. Forest industry members include Ainsworth Engineered Canada LP., Alberta-Pacific Forest Industries Inc., Canadian Forest Products Ltd., Daishowa-Marubeni International Ltd., Footner Forest Products Ltd., Millar Western Forest Products Ltd., Tolko Industries Ltd., Slave Lake Pulp/Alberta Plywood Ltd., Vanderwell Contractors (1971) Ltd. and Weyerhaeuser Company Ltd. The Alberta government and the University of Alberta are supporting partners in the Association. The Association's goals are to increase knowledge of aspen/white spruce mixed forests in the areas of growth and yield, crop planning, monitoring, understory protection and decision support tools. This paper highlights some of the Association-sponsored research projects. Key words: Alberta, Mixedwood Management Association, research, growth and yield, crop plans
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".