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Record W2101461733 · doi:10.1002/9780470057339.vnn170

Soil Contamination and Remediation

2012· other· en· W2101461733 on OpenAlexaff
Francis Zvomuya, Alison P. Murata

Bibliographic record

VenueEncyclopedia of Environmetrics · 2012
Typeother
Languageen
FieldEnvironmental Science
TopicMicrobial bioremediation and biosurfactants
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsContaminationEnvironmental remediationEnvironmental scienceSoil contaminationEnvironmental chemistryGroundwater contaminationContaminated landPollutionSoil waterGroundwaterEcologyChemistryAquiferSoil scienceGeologyBiology

Abstract

fetched live from OpenAlex

Abstract Soil contamination is a major concern across the globe because it poses a severe threat to human and environmental health. Organisms that come into direct or indirect contact with contaminated soil or its associated groundwater may be negatively impacted. Soil contamination is also a problem because it reduces the quality and productivity of natural and agricultural ecosystems. Although soil contamination can be caused by natural processes and events, most contamination is the result of anthropogenic activities. Sites may be contaminated with a variety of contaminants, which are grouped into two categories: inorganic and organic. Inorganic contaminants include trace elements and radionuclides, whereas organic contaminants include polycyclic aromatic hydrocarbons (PAHs), petroleum hydrocarbons, and pesticides. Trace elements and PAHS are the most abundant and widespread contaminants. When sites are found to be contaminated, a wide variety of remediation strategies exists to address the problem. This article discusses some of the more common technologies used to treat contaminated soils.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.183
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)0.0170.001

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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2012
Admission routes1
Has abstractyes

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