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Record W2774672006 · doi:10.3390/agronomy7040081

Starch Biosynthesis in the Developing Endosperms of Grasses and Cereals

2017· article· en· W2774672006 on OpenAlexafffund
Ian J. Tetlow, Michael J. Emes

Bibliographic record

VenueAgronomy · 2017
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Guelph
KeywordsAmyloplastStarchEndospermPoaceaeDomesticationAgronomyPopulationBiologyCaryopsisCropSorghumAgricultureBotanyFood scienceEcologyPlastidBiochemistryChloroplast

Abstract

fetched live from OpenAlex

The starch-rich endosperms of the Poaceae, which includes wild grasses and their domesticated descendents the cereals, have provided humankind and their livestock with the bulk of their daily calories since the dawn of civilization up to the present day. There are currently unprecedented pressures on global food supplies, largely resulting from population growth, loss of agricultural land that is linked to increased urbanization, and climate change. Since cereal yields essentially underpin world food and feed supply, it is critical that we understand the biological factors contributing to crop yields. In particular, it is important to understand the biochemical pathway that is involved in starch biosynthesis, since this pathway is the major yield determinant in the seeds of six out of the top seven crops grown worldwide. This review outlines the critical stages of growth and development of the endosperm tissue in the Poaceae, including discussion of carbon provision to the growing sink tissue. The main body of the review presents a current view of our understanding of storage starch biosynthesis, which occurs inside the amyloplasts of developing endosperms.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.288
Teacher spread0.241 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations113
Published2017
Admission routes2
Has abstractyes

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