Preliminary Assessment on the Conservation Status of Canadian Medicinal Plants
Bibliographic record
Abstract
The objective of the current study was to provide a preliminary assessment on the conservation status of Canadian medicinal plants in order to help guide future efforts to protect biocultural diversity in Canada. Using data provided from the Native American Ethnobotany Database (http://naeb.brit.org/), United States Department of Agriculture (https://plants.usda.gov) and Natureserve (http://explorer.natureserve.org/), a comprehensive assessment on the conservation status and distribution of Canadian medicinal plants was performed. Using this approach 1446 medicinal plants were identified in Canada, with the greatest number being located in Ontario (n = 1042), British Columbia (n = 882), and Quebec (n = 854). Of these, 54% had a Natureserve ranking as secure (S5), while 17% were currently unranked (SNA, SNR). The number of species ranked by Natureserve varied by province, with over 93% and 84% of medicinal species located in the Northwest Territories and Nunavut having not been assessed (SNA, SNR, SU) respectively. While the above is a good start to understanding the distribution and vulnerability of Canadian medicinal plants and to prioritize specific species/ecosystems for future monitoring, these databases do not fully reflect Canadian specific biodiversity information. Thus, greater effort is needed in the future to reconcile ethnobotanical, species distribution and conservation information for Canadian species within one place, as there is currently no centralized system to monitor the distribution and conservation status of medicinal flora.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".