Chemical Form of Selenium in Naturally Selenium-Rich Lentils (<i>Lens culinaris</i> L.) from Saskatchewan
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".