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Record W2074718427 · doi:10.1080/07373930701831457

Optimum Processing Conditions of Instant Asian Noodles in Superheated Steam

2008· article· en· W2074718427 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

VenueDrying Technology · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Manitoba
Fundersnot available
KeywordsSuperheated steamInstantFood scienceStarchChemistrySuperheatingMathematicsMaterials sciencePulp and paper industryEngineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

There is little information in the literature about what constitutes an acceptable instant noodle. To ascertain the commercial acceptability of superheated steam-processed instant noodles, a sampling of commercial products was undertaken. Noodles processed at a steam velocity of 1.5 m/s and at 125°C for 200 s, 130°C for 167 s, 135°C for 150 s, 140°C for 133 s, 150°C for 100 s, and a steam velocity of 1.0 m/s and 150°C for 133 s had acceptable color values (L∗ values greater than 63, a∗ values less than 0, and b∗ values above 20) and moisture at or below the safe storage limit. Superheated steam processed noodles were more firm and chewy than the commercial noodles. Adhesiveness, springiness, and resilience were generally the same for all noodle products. Breaking strength of superheated steam processed noodles was in the same range as the fried control and commercial products. Values varied from a low of 1121 ± 194 g/mm2 for noodles processed at 150°C, 1.5 m/s, for 100 s to a high of 1575 ± 329 g/mm2 for noodles processed at 140°C, 1.5 m/s, for 133 s. Starch gelatinization was greatest in the fried control samples and the least in the superheated steam processed samples (approximately 9% less).

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.659
Threshold uncertainty score0.171

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 head0.037
GPT teacher head0.249
Teacher spread0.212 · 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