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Record W2322815439 · doi:10.1021/es203904e

Production and Release of Selenocyanate by Different Green Freshwater Algae in Environmental and Laboratory Samples

2012· article· en· W2322815439 on OpenAlexaff
Kelly L. LeBlanc, Matthew S. Smith, Dirk Wallschläger

Bibliographic record

VenueEnvironmental Science & Technology · 2012
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsTrent University
Fundersnot available
KeywordsAlgaeSeleniumSelenateEnvironmental chemistryGreen algaeScenedesmusChlorellaBotanyBrown algaeChemistryChlorella vulgarisSpirogyraBioaccumulationBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

In a previous study, selenocyanate was tentatively identified as a biotransformation product when green algae were exposed to environmentally relevant concentrations of selenate. In this follow-up study, we confirm conclusively the presence of selenocyanate in Chlorella vulgaris culture medium by electrospray mass spectrometry, based on selenium's known isotopic pattern. We also demonstrate that the observed phenomenon extends to other green algae (Chlorella kesslerii and Scenedesmus obliquus) and at least one species of blue-green algae (Synechococcus leopoliensis). Further laboratory experiments show that selenocyanate production by algae is enhanced by addition of nitrate, which appears to serve as a source of cyanide produced in the algae. Ultimately, this biotransformation process was confirmed in field experiments where trace amounts of selenocyanate (0.215 ± 0.010 ppb) were observed in a eutrophic, selenium-impacted river with massive algal blooms, which consisted of filamentous green algae (Cladophora genus) and blue-green algae (Anabaena genus). Selenocyanate abundance was low despite elevated selenium concentrations, apparently due to suppression of selenate uptake by sulfate, and insufficient nitrogen concentrations. Finally, trace levels of several other unidentified selenium-containing compounds were observed in these river water samples; preliminary suggestions for their identities include thioselenate and small organic Se species.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.962

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 studies0.0000.003
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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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 designBench or experimental
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

Citations17
Published2012
Admission routes1
Has abstractyes

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