Berries as a case study for crop wild relative conservation, use, and public engagement in Canada
Bibliographic record
Abstract
Societal impact statement Plant biodiversity is fundamental to the future of food security and agriculture. Berries are the most economically important fruit crops in Canada. Within this article, we explore the nutritional, cultural, and botanical importance of berries, including crop wild relatives (plant species that are closely related to domesticated crops) and plants that are significant to Indigenous Peoples. Using berries as a case study, we explore opportunities for the conservation, use, and public engagement of crop wild relatives. Our objective is to lay the groundwork for future collaborative efforts across these diverse plants. Summary Conservation of plant biodiversity, in particular crop wild relatives including those tended and cultivated by Indigenous Peoples, is critical to food security and agriculture. Building on the 2019 road map for crop wild relatives, we examine berries as a case study for crop wild relative conservation, use, and public engagement. We focus on berries due not only to their economic, cultural, and nutritional importance but also because they are consumed fresh, providing a unique opportunity for individuals and communities to connect with plants. We outline health benefits, geographic distribution, and species at risk for Canadian berries. We describe practices, strategies, and approaches used by Indigenous Peoples to steward berries and emphasize the importance of traditional knowledge. We highlight opportunities for in situ and ex situ berry conservation and use of berries in plant breeding and Indigenous foodways. Our aim is to lay the groundwork for future collaborative efforts in these areas and to showcase berries as a useful case study for conservation of food plant biodiversity and public engagement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.029 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".