316 A 99-year journey on the use of by-product feeds in Canadian livestock production
Bibliographic record
Abstract
Abstract For centuries livestock have had a significant role as ‘upcyclers’, with the ability to convert inedible food into high quality protein in the form of meat, milk, or fiber. Currently, a large portion of the feed utilized in livestock production systems includes grains, pulses and oilseeds, as well as other commodities that fail to reach the quality grade required for human consumption. In addition to these on-farm or near farm losses, by-products from food and industrial processing including alcohol and biofuel production, oilseeds, as well as fruit and vegetable processing generate significant waste. The Canadian livestock industry has progressed from using these by-products of crop production and food processing, to including surplus food that is redirected from landfills to livestock feed. In Canada, total annual food loss and waste equates to 35.5 million MT of which 32% is avoidable. Food loss is associated with low-quality or human indigestible by-products during the production, processing, and distribution stages of the supply chain, whereas food waste is defined as food that is not consumed at the retail, food service, and consumer stages of the food supply chain. Diverting food loss and waste to livestock and poultry feed has important environmental, economic, and social impacts, including improved global food security, and decreasing greenhouse gas and ammonia emissions, as well as land and water use. There are global efforts to improve the utilization of both food loss and waste, however, challenges exist including economic viability, collection and distribution logistics, regulatory restrictions, and feed safety. A coordinated approach between livestock producers, food processors, feed suppliers, researchers, policy makers and retailers is critical for the development of successful strategies for inclusion of food loss and waste in livestock diets.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.014 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 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".