Research, development, and deployment needs for short-rotation plantation and agroforestry systems: an experts’ assessment of landowners’ perceptions
Bibliographic record
Abstract
A survey was conducted among 126 experts to assess a comprehensive array of 44 research, development, and deployment (RD&D) needs previously identified by landowners (Marchand and Masse 2008) for four short-rotation plantation or agroforestry systems based on willow or hybrid poplar in Canada. Among the 44 initial needs, the study identified 16 needs that a significant majority of the experts who commented on them considered relevant to address in the short term (0–5 years), of which 11 needs applied to at least two of the four systems, half pertained to research and development, half to deployment, and most were related to economic or technical issues. The relevance of addressing these needs was expected to either remain stable or increase over the medium term (6–10 years). The needs identified in this study give a comprehensive overview of RD&D priorities for each of the four systems in Canada. As such, they should be useful for determining research directions and deployment policies and for designing broad program components. An updated list of needs is provided to facilitate the examination of potential need–system combinations other than those assessed as relevant.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".