Greenhouse gas emissions from Canada agriculture narrowing the knowledge gaps - Final program and research report for the Climate Change Funding Initiative in Agriculture (CCFIA)
Bibliographic record
Abstract
In February 2000 the Canadian Agri-Food Research Council (CARC) accepted an invitation from Agriculture and Agri-Food Canada to deliver the Climate Change Funding Initiative in Agriculture (CCFIA). At that time, climate change research was still a relatively new area, particularly for agriculture. In the four years since, research activities in all areas have grown exponentially, with added urgency given as a result of Canada’s commitment to the Kyoto Protocol to the United Nations Framework Convention on Climate Change. Through its Canadian Adaptation and Rural Development (CARD) II program, Agriculture and Agri-Food Canada provided funding of $4 million over four years to CARC for the CCFIA. The funding was used to support development of human resources, for research projects, and for communications activities. CARC’s Canada Committees initiated activities to coordinate climate change activities in Canadian agriculture, including the development of three major position papers, as well as a process to identify research and development needs that are not being currently addressed or that require increased attention. This report provides summaries of the individual research projects of this program.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".