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Record W4378078166 · doi:10.3390/foods12102087

Research Progress of Quinoa Seeds (Chenopodium quinoa Wild.): Nutritional Components, Technological Treatment, and Application

2023· review· en· W4378078166 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

VenueFoods · 2023
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicSeed and Plant Biochemistry
Canadian institutionsAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsChenopodium quinoaAmaranthBiologyFood scienceDietary fiberBiotechnologyAgronomy

Abstract

fetched live from OpenAlex

Wild.) is a pseudo-grain that belongs to the amaranth family and has gained attention due to its exceptional nutritional properties. Compared to other grains, quinoa has a higher protein content, a more balanced amino acid profile, unique starch features, higher levels of dietary fiber, and a variety of phytochemicals. In this review, the physicochemical and functional properties of the major nutritional components in quinoa are summarized and compared to those of other grains. Our review also highlights the technological approaches used to improve the quality of quinoa-based products. The challenges of formulating quinoa into food products are addressed, and strategies for overcoming these challenges through technological innovation are discussed. This review also provides examples of common applications of quinoa seeds. Overall, the review underscores the potential benefits of incorporating quinoa into the diet and the importance of developing innovative approaches to enhance the nutritional quality and functionality of quinoa-based products.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.161
GPT teacher head0.370
Teacher spread0.208 · 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