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Record W2142945524 · doi:10.5539/ep.v1n2p61

Potential Effects of Environmental Change on Mining Wastes in a Hyperarid Climate

2012· article· en· W2142945524 on OpenAlexvenueno aff
Douglas B. Sims, Peter S. Hooda, Gavin Gillmore

Bibliographic record

VenueEnvironment and Pollution · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoal and Its By-products
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental sciencePrecipitationStormClimate changeSedimentHydrology (agriculture)AridGeologyOceanographyMeteorologyGeographyGeomorphology

Abstract

fetched live from OpenAlex

Three desert washes were sampled to evaluate the transport of contaminated sediments from abandoned mining sites to downwash environments. The area of concern is an extreme arid climate considered stable and not to pose pathways for contaminated sediments to impact downwash environments. Research of mine wastes in Nelson, Nevada has shown that residual geogenic and anthropogenic trace elements have been mobilized in surface sediments as a result of storm event. Cyanide and trace elements, especially mercury and lead, have transported to 6000 m downwash from source areas. Short term environmental impacts appear to be minimal because of present-day environmental conditions. However, climate shifts caused by the El Nino Southern Oscillations or even a dramatic climate shift might increase regional precipitation promoting a more rapid erosion of contaminated sediment. Currently, wash sediments do not contain levels of CN- or trace elements that pose threats to the environment; however, if erosion and transport of mining waste increased because of additional precipitation, then CN- and trace elements loading in storm water would increase, with their possibly delivery to Lake Mohave.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.351

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)0.0000.000

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.

Opus teacher head0.009
GPT teacher head0.164
Teacher spread0.155 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2012
Admission routes1
Has abstractyes

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