The Canadian Forest Service: Agent of change in an evolving forest environment
Bibliographic record
Abstract
The Canadian Forest Service (CFS) has set new goals and priorities in its Strategic Plan 20032008, re-examining the knowledge it creates and the ways in which that knowledge is created. This is in line with the Government of Canada's pursuit of a global strategy for Canadian science and technology, supporting more collaborative international research at the frontiers of knowledge. Also, with the Canadian forest industry facing new and non-traditional competitors and repositioning its product mix, CFS is encountering increased expectations from its external partners, clients and stakeholdersas the primary forest research agency in the country and the main federal body ensuring the competitiveness of the industry. CFS is, therefore, re-defining its role as the leading player in the Canadian forest sector by re-evaluating how it does business. CFS will spearhead the development and implementation of a new national forest S&T agenda, becoming Canada's premier source of authoritative, value-added forest information. It will also champion Canadian forest interests and expertise internationally while strengthening national consensus on Canadian forest policies and programs and advocating Canada's forest agenda within the federal government. To this end, CFS will attract and support talented personnel by creating a workplace conducive to creativity. Key words: Strategic Plan, global S&T strategy, non-traditional competitors, product mix, value-added forest information
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".