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Record W4200407095 · doi:10.1002/ecs2.3880

Collaboration with Nlaka'pamux communities to examine metal deposition on soapberry in interior British Columbia

2021· article· en· W4200407095 on OpenAlexaffabout
Kevan Berg, Shanti Berryman, Ann Garibaldi, Justin Straker, Natalie Melaschenko, Jay M. Ver Hoef

Bibliographic record

VenueEcosphere · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsVictoria General Hospital
Fundersnot available
KeywordsEnvironmental chemistryDeposition (geology)Soil waterEnvironmental scienceMetalResource (disambiguation)Inductively coupled plasma mass spectrometryChemistryGeologySoil scienceMass spectrometrySediment

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.777
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.001

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.

Opus teacher head0.007
GPT teacher head0.206
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes2
Has abstractyes

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