Traditional Uses of Medicinal Plants from the Canadian Boreal Forest for the Management of Chronic Pain Syndromes
Bibliographic record
Abstract
OBJECTIVE: Chronic pain is more prevalent in indigenous populations who often prefer traditional remedies over allopathic drugs. Our objective was to investigate the traditional uses of medicinal plants from the Canadian boreal forest for the management of chronic pain syndromes. METHODS: We reviewed the most extensive database on medicinal plants used by aboriginal people of the Canadian boreal forest to investigate the plants used in the management of 3 of the most common chronic pain syndromes: arthritis/rheumatism; back pain; and headache/migraine. We also reviewed the pharmacology and phytochemistry literature to investigate concordance with indigenous knowledge. RESULTS: A total of 114 medicinal plant species were reported, of which 27 (23.5%) were used to treat more than 1 chronic pain syndrome. Pharmacological or phytochemical evidence to explain plant function as chronic pain remedy was available in the literature for only 38 species (33%), with several species reported to have anti-inflammatory and analgesic properties effective in treating chronic pain syndromes. CONCLUSIONS: Our study showed the potential of boreal plants as alternative and complementary medicines for the treatment of chronic pain syndromes that could be enhanced by further research on efficacy and safety issues.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".