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Record W3145408155 · doi:10.1111/1541-4337.12748

Selenium in cereals: Insight into species of the element from total amount

2021· review· en· W3145408155 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.

Bibliographic record

VenueComprehensive Reviews in Food Science and Food Safety · 2021
Typereview
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBiofortificationSeleniumBioavailabilityMicronutrientFood scienceHuman healthBiologyTrace elementHuman nutritionToxicityEnvironmental chemistryChemistryToxicologyAgronomy

Abstract

fetched live from OpenAlex

Selenium (Se) is a trace mineral micronutrient essential for human health. The diet is the main source of Se intake. Se-deficiency is associated with many diseases, and up to 1 billion people suffer from Se-deficiency worldwide. Cereals are considered a good choice for Se intake due to their daily consumption as staple foods. Much attention has been paid to the contents of Se in cereals and other foods. Se-enriched cereals are produced by biofortification. Notably, the gap between the nutritional and toxic levels of Se is fairly narrow. The chemical structures of Se compounds, rather than their total contents, contribute to the bioavailability, bioactivity, and toxicity of Se. Organic Se species show better bioavailability, higher nutritional value, and less toxicity than inorganic species. In this paper, we reviewed the total content of Se in cereals, Se speciation methods, and the biological effects of Se species on human health. Selenomethionine (SeMet) is generally the most prevalent and important Se species in cereal grains. In conclusion, Se species should be considered in addition to the total Se content when evaluating the nutritional and toxic values of foods such as cereals.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.983
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.115
GPT teacher head0.343
Teacher spread0.228 · 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