Life Cycle Assessment of Oat Flake Production with Two End-of-Life Options for Agro-Industrial Residue Management
Bibliographic record
Abstract
Canada is one of the world’s largest producers of oat (Avena sativa L.) grains and their derivatives, such as oat flakes. During oat flake production, considerable amounts of residue are generated, which constitutes a major issue for producers. We applied life cycle assessment (LCA): (1) to quantify the environmental impacts of oat flakes production in northeastern Canada and (2) to compare two agro-industrial symbiosis scenarios applied to agricultural residues (transformation of residues into feed for farm animals vs. composting). LCA results indicated that the environmental impacts of oat flake production are largely dominated by the production and use of synthetic fertilisers (contributing to at least 50% of the impact of each evaluated category). Regarding end-of-life scenarios, an environmental advantage is observed for the scenario of residue transformation into animal feed in the provinces of Quebec and Manitoba. However, this recommendation may change depending on the electricity mix used and the assumptions made for the avoided products. The choice of industrial symbiosis chains must take into consideration the economic characteristics of the region where they will be implemented and the methodological parameters that can influence the decision-making process.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".