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Record W4406106423 · doi:10.1093/inteam/vjae005

Regulatory issues surrounding the management of selenium—introduction to a special series of papers

2025· article· en· W4406106423 on OpenAlexaff
Guy Gilron, Vince Palace

Bibliographic record

VenueIntegrated Environmental Assessment and Management · 2025
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsInternational Institute for Sustainable DevelopmentCollège Boréal
Fundersnot available
KeywordsSeleniumSeries (stratigraphy)Environmental planningEnvironmental scienceGeologyChemistry

Abstract

fetched live from OpenAlex

Selenium (Se) is a naturally occurring metalloid in soils and rocks that is released by weathering processes; it is also enriched by some anthropogenic activities, including mining and agriculture. The mechanism of Se aquatic toxicity has been understood for several decades; at elevated concentrations, dietary Se can accumulate in maternal tissues of fish and birds, become deposited into their eggs, and can potentially result in impaired embryological development. North American environmental regulations have acknowledged differences in species sensitivity and variation among aquatic environments (i.e., lentic and lotic) that influence Se toxicity. The above subjects were thoroughly reviewed in a state-of-science SETAC Pellston workshop and book, entitled Ecological assessment of selenium in the aquatic environment, published in 2010. Since the publication of that book, regulatory guidance in North America has evolved further to enhance the protection of aquatic life exposed to Se. This IEAM special series entitled "Regulatory issues surrounding the management of selenium" is a compilation of recent research and reviews from North American experts addressing critical environmental, physiological, and operational factors warranting consideration in support of Se regulatory frameworks.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.634

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 head0.008
GPT teacher head0.255
Teacher spread0.247 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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