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Record W2021813846 · doi:10.1081/drt-120038571

Drying Foodstuffs with Superheated Steam

2004· article· en· W2021813846 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 · 2004
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSuperheated steamPulp (tooth)Pulp and paper industrySugar beetStarchSugarMaterials scienceBoiler (water heating)ChemistryComposite materialFood scienceHorticultureWaste managementMedicineEngineering

Abstract

fetched live from OpenAlex

Abstract A thin-layer superheated steam drier was constructed with the objective of determining the drying characteristics, drying rates, and the effect of superheated steam on product quality in thin-layers. Results from superheated steam drying experiments with sugar-beet pulp, potatoes, Asian noodles, and spent grains indicate that drying times and rates increase with increasing steam temperature. For sugar-beet pulp it was also found that these changes were more significant than increases seen by hot-air drying under the same conditions and that drying rates were not affected by velocity for hot air but were increased for superheated steam. When quality aspects were examined, superheated steam dried Asian noodles saw both beneficial changes to recovery, adhesiveness, and gumminess while parameters of maximum cutting stress, resistance to compression, and surface firmness saw deleterious effects. Spent grains saw high levels of starch gelatinization and retention of fibre content.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.286

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 head0.010
GPT teacher head0.182
Teacher spread0.172 · 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