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Record W2073940629 · doi:10.1021/jf070681i

Chemical Form of Selenium in Naturally Selenium-Rich Lentils (<i>Lens culinaris</i> L.) from Saskatchewan

2007· article· en· W2073940629 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2007
Typearticle
Languageen
FieldNursing
TopicSelenium in Biological Systems
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsSeleniumSelenateMicronutrientArsenicChemistryBiofortificationFood scienceHuman healthX-ray absorption spectroscopyEnvironmental chemistryBotanyBiologyAbsorption spectroscopy

Abstract

fetched live from OpenAlex

Lentils (Lens culinaris L.) are a source of many essential dietary components and trace elements for human health. In this study we show that lentils grown in the Canadian prairies are additionally enriched in selenium, an essential micronutrient needed for general well-being, including a healthy immune system and protection against cancer. Selenium K near-edge X-ray absorption spectroscopy (XAS) has been used to examine the selenium biochemistry of two lentil cultivars grown in various locations in Saskatchewan, Canada. We observe significant variations in total selenium concentration with geographic location and cultivar; however, almost all the selenium (86-95%) in these field-grown lentils is present as organic selenium modeled as selenomethionine with a small component (5-14%) as selenate. As the toxicities of certain forms of arsenic and selenium are antagonistic, selenium-rich lentils may have a pivotal role to play in alleviating the chronic arsenic poisoning in Bangladesh.

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)0.000
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 score0.094
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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