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Record W2589624567 · doi:10.1002/mnfr.201600767

Phytochemicals in quinoa and amaranth grains and their antioxidant, anti‐inflammatory, and potential health beneficial effects: a review

2017· review· en· W2589624567 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Nutrition & Food Research · 2017
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsAmaranthChenopodium quinoaPhytochemicalMicronutrientAmaranthus cruentusFood scienceAntioxidantCarotenoidNutrientBiologyEssential nutrientChemistryBotanyBiochemistry

Abstract

fetched live from OpenAlex

Quinoa (Chenopodium quinoa Willd.) and amaranth (Amaranthus cruentus L.) are pseudocereal grains rich in both macronutrients and micronutrients including vitamins and minerals. The proteins are particularly of high nutritional quality due to the outstanding balance of essential amino acids. However, recent research strongly suggests that nonessential nutrients such as phytochemicals of quinoa and amaranth may also have potential health beneficial effects. This review focuses on the phytochemical composition of quinoa and amaranth seeds, the antioxidant and anti-inflammatory activities of hydrophilic (e.g. phenolics, betacyanins) and lipophilic (e.g. fatty acids, tocopherols, and carotenoids) nutrients, and how these contribute to the potential health benefits, especially in lowering the risk of the oxidative stress related diseases e.g. cancer, cardiovascular disease, diabetes, and obesity. The gap between current knowledge and future research needs have also been identified.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.887
Threshold uncertainty score0.692

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.078
GPT teacher head0.363
Teacher spread0.285 · 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