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Energy Consumption, Density, and Rehydration Rate of Vacuum Microwave‐ and Hot‐Air Convection‐ Dehydrated Tomatoes

2002· article· en· W2142162114 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

VenueJournal of Food Science · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDehydrationMicrowaveBoilingConvectionChemistryEnergy consumptionVacuum levelProcess (computing)Materials sciencePulp and paper industryMeteorologyPhysicsElectrical engineeringBiochemistry

Abstract

fetched live from OpenAlex

ABSTRACT: Vacuum to lower boiling temperature and microwaves for energy transfer can provide very rapid dehydration at low temperatures. Tomato sections were dehydrated in a batch convection air dryer (AD), a 16 kW vacuum microwave (VM) dryer, or by 1 of 3 combination processes. Drying rate of the 100% VM process was 18 times that of the 100% AD process. Only a slight falling rate effect was noted in VM drying AD and VM in sequence allowed the operator to choose any process time between 0.8 and 14.75 h. In this instance the least energy consumption occurred in the 100% VM process. Lowest energy cost was found for the 70% AD / 30% VM process. These results are expected to be strongly dependent upon the scale and design of dryers. Tomatoes finish‐dried by VM exhibited a puffed structure associated with faster rehydration.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.181

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.030
GPT teacher head0.214
Teacher spread0.184 · 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