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Record W2109837306 · doi:10.1270/jsbbs.59.179

Screening and characterization of cultivar with M-type amylopectin in Japanese upland rice

2009· article· en· W2109837306 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.

Bibliographic record

VenueBreeding Science · 2009
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsPlant Biotechnology Institute
FundersMinistry of Agriculture, Forestry and Fisheries
KeywordsAmylopectinCultivarOryza sativaStarchBiologyResistant starchHorticultureFood scienceBotanyAgronomyAmyloseGeneBiochemistry

Abstract

fetched live from OpenAlex

Asian rice (Oryza sativa L.) cultivars were recently classified into L-type, S-type, and intermediate M-type (rich, poor and middle intermediate-chain) on the basis of the fine structure of amylopectin in their grains. We selected 4 cultivars with M-type amylopectin from 174 local Japanese nonwaxy upland rice cultivars by scoring the disintegration of starch granules in alkaline solution and measuring the pasting temperature (PT) of their rice flours. Analyzed amylopectin fine structure, these cultivars exhibited intermediate characteristics between those of S-type Koshihikari and L-type IRAT109. Moreover, compared hardness of dumpling cakes after cooled for 3 h and 24 h. The hardness was in the order L-type > M-type > S-type, each other. On the other hand, the amylopectin chain ratio (ACR) was negatively correlated with the hardness of dumpling cakes both after cooled for 3 h and 24 h. Therefore, we concluded that the 4 cultivars—Chikanarijyun1, Hokkaiakage, Kairyo13, and Mogamichikanari1—had M-type amylopectin, and Japanese local upland rice has wide genetic diversity about starch mutation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.177

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.255
Teacher spread0.232 · 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