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Record W3164047250 · doi:10.3390/w13111473

Environmental Impacts of Selenium Contamination: A Review on Current-Issues and Remediation Strategies in an Aqueous System

2021· review· en· W3164047250 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWater · 2021
Typereview
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsStantec (Canada)University of Calgary
FundersPetroleum Technology Development FundNatural Sciences and Engineering Research Council of Canada
KeywordsSeleniumEnvironmental chemistryContaminationEnvironmental scienceEnvironmental remediationBioremediationPollutantChemistryEcologyBiology

Abstract

fetched live from OpenAlex

In both aquatic and terrestrial environment, selenium contamination may exist at concentrations above the micronutrient limit. Since there is such a narrow bandwidth between which selenium concentration is acceptable, the health of the public may be at risk of selenium toxicity once the concentration increases beyond a threshold. Selenium contamination in an aqueous environment can occur due to anthropogenic activities and/or from natural sources. This study presents a review of the forms of selenium, inorganic and organic selenium contamination, mobilization, analytical methods for various forms of selenium and remediation strategies. The review also provides recent advances in removal methods for selenium from water including bioremediation, precipitation, coagulation, electrocoagulation, adsorption, nano-zerovalent iron, iron co-precipitation and other methods. A review of selenomethionine and selenocysteine removal strategy from industrial wastewaters is presented. Selenium resource recovery from copper ore processing has been discussed. Various analytical methods used for selenium and heavy metal analysis were compared. Importantly, existing knowledge gaps were identified and prospective areas for further research were recommended.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.798
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.044
GPT teacher head0.339
Teacher spread0.295 · 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