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Establishment of a Vegetation Cover on Tundra Kimberlite Mine Tailings: 1. A Greenhouse Study

2005· article· en· W1967527800 on OpenAlexaffabout
Neil Reid, M. Anne Naeth

Bibliographic record

VenueRestoration Ecology · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of AlbertaVanguard College
Fundersnot available
KeywordsTailingsEnvironmental scienceTundraPeatVegetation (pathology)Subarctic climateEcosystemEcologyBiologyChemistry

Abstract

fetched live from OpenAlex

Abstract High erosion potential of dewatered kimberlite mine tailings after diamond extraction has prompted research at the Ekati Diamond Mine in the Canadian subarctic heath tundra ecosystem. Coarse texture, no organic component, lack of available macronutrients, and a serpentine chemistry are the principal limitations of these kimberlite tailings to plant colonization. Structure‐improving (peat moss, lake sediment, sewage sludge, Agri‐Boost, and composted papermill sludge) and nutrient‐providing (fertilizer, calcium carbonate, gypsum, and rock phosphate) amendments were tested in the greenhouse to ameliorate these limitations, thereby facilitating the field establishment of a permanent vegetation cover, which would stabilize the surface materials and promote natural colonization by the surrounding tundra vegetation. Seven native grass species ( Arctagrostis latifolia , Calamagrostis canadensis , Poa glauca , Poa alpina , Deschampsia beringensis , Deschampsia caespitosa , and Festuca rubra ) were used to measure amendment success. With the addition of structure‐improving and nutrient‐providing amendments, plant growth on kimberlite tailings was significantly enhanced. Tailings properties, including cation exchange capacity, percentage of organic carbon, and macronutrient availability, were also improved by amendment addition.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
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)0.0010.001

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 head0.011
GPT teacher head0.244
Teacher spread0.234 · 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; a candidate call from one teacher head, not a consensus.

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

Citations32
Published2005
Admission routes2
Has abstractyes

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