Collaboration with Nlaka'pamux communities to examine metal deposition on soapberry in interior British Columbia
Bibliographic record
Abstract
Abstract This paper presents a collaboration with Indigenous Nlaka'pamux communities to develop a study to address the effects of mining dust on soapberry ( Shepherdia canadensis ), which is an important medicinal and food resource for local Nlaka'pamux people. The objectives were to compare element concentrations in samples of washed and unwashed leaves and berries relative to soil samples collected around the mine and in a reference area. Samples were analyzed for metal concentrations using inductively coupled plasma mass spectrometry (ICP‐MS). Spatial models showed that six metals (Al, Ba, Cu, Fe, Pb, and Sr) had significant elevated concentrations near the mine compared to farther away, though concentrations were generally within ranges reported for human consumption. There was no correspondence with soil metal concentrations, suggesting that elevated metal concentrations in leaves and berries near the mine were due to dust rather than uptake from local soils. Washing of leaves and berries reduced concentrations by between 13 and 48%, depending on the metal. The study illustrates a model with global relevance for how mines can work with communities to address complex social–ecological problems.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".