An assessment of the opportunities and challenges of a bio-based economy for Agriculture and Food Research in Canada
Bibliographic record
Abstract
The replacement of petrochemical-based industrial chemicals with chemicals derived from renewable biological materials is a very worthy and alluring objective. The reduction of greenhouse gases (GHG), the lessening of dependence on non-renewable resources, the increase in markets for farm products, and the potential for new industries in widely distributed geographic locations across the nation are all outcomes which are attractive to many Canadians. This study, commissioned by the Canadian Agri-Food Research Council (CARC) and the BIOCAP Canada Foundation (BIOCAP), is intended to give Canadian researchers, legislators and the public in general a better understanding of the research issues involved in this highly complex industry. Specific effort has been made to focus the study on a selected number of industrial sectors which might play an important role, not only in the control of GHG emissions, but also in providing new economic opportunities to farmers and rural communities. The potential role for biofuels including ethanol, biodiesel, methane and other bioenergy sources have been given specific attention. Also covered in this study are bioplastics, bioadhesives, biocomposites, biolubricants and platform chemicals; all sectors which could have a significant contribution to an evolving bio-based economy. Sectors such as pharmaceuticals, cosmetics, nutraceuticals, surfactants, and bio-based inks, (all of great interest to many researchers and business leaders) are not covered due to the attention they continue to receive elsewhere, and their relatively modest impact on GHG and other climate issues. The work covered in this report was deliberately focussed on research and development. Market and economic topics are touched on for context purposes, but are not dealt with in any depth, as they are the focus of other studies currently in progress. Specifically, Agriculture and Agri-Food Canada (AAFC), with assistance from Industry Canada, is currently supporting a major study aimed at identifying commercial opportunities in the same sectors as are the focus of this study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".