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Record W2785651669 · doi:10.5539/jas.v10n3p16

Characteristics of Rice Flour Breads Using Yeast Isolated from Pear Red Bartlett Fruits

2018· article· en· W2785651669 on OpenAlex
Takeshi Nagai, Norihisa Kai, Yasuhiro Tanoue, Nobutaka Suzuki

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Agricultural Science · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsnot available
FundersJapan Society for the Promotion of Science
KeywordsFood scienceAmylosePEARGlutenCultivarStarchChemistryWheat flourYeastRice flourHorticultureBiologyRaw material

Abstract

fetched live from OpenAlex

To develop high qualities of rice flour breads, we tried to prepare breads using rice flours from major five non-glutinous rice cultivars on market shares of Japan and wild-type Saccharomyces cerevisiae strain YTPR1 isolated from pear Red Bartlett fruits. Apparent amylose contents of rice flours were measured about 12.1-19.9%. Damaged starch contents of these flours were about 22% regardless to the kinds of rice cultivars. Gluten was added about 20 wt.% based on rice flour, and breads were made in the same way. Any bread has caused caving. Next, the amount of water added in dough was regulated in consideration of moisture contents of rice flours. Except for Akitakomachi flour, breads largely expanded, although loaves volumes did not amount to that on bread made from bread flour and commercially available baker’s dried yeast. It was observed correlation between the amount of water and amylose contents of rice flours with R2 = 0.703. It suggested that the amount of water added in dough might estimate from amylose contents of rice flours. Specific volumes of these loaves were low compared with that made from bread flour. However, by sensory analysis, breads made from Hinohikari and Haenuki flours had total points closest to that made from bread flour: it could produce high quality of breads using Hinohikari and Haenuki flours and yeast isolated from pear Red Bartlett fruits.

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)0.001
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 score0.976
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.037
GPT teacher head0.254
Teacher spread0.218 · 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