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Record W2096966381 · doi:10.1080/07373930601119912

Gaseous Carbon Dioxide as the Heat and Mass Transfer Medium in Drying

2007· article· en· W2096966381 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 · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsCarbon dioxideMass transferGrain dryingHeat transferFluidized bedWet-bulb temperatureMaterials scienceDry-bulb temperatureEnvironmental scienceWaste managementPulp and paper industryThermodynamicsChemistryComposite materialChromatographyHumidityEngineering

Abstract

fetched live from OpenAlex

Using available correlations for heat transfer, a comparative analysis of drying rates in CO2 and in air was performed for several basic types of dryers. Higher heat transfer rates were found for dryers with active hydrodynamics, which translates into shorter drying time for materials dried in the first drying period. These results were validated by experiments on drying wheat kernels fluidized by air and by CO2. Shorter drying times by about 20% were confirmed for CO2, which offers energy savings of about 3% of the heat input to the dryer. Additional energy savings of 4% of the heat load can be expected for drying at temperatures below 100°C because of the lower wet-bulb temperature for CO2 than that for air. The potential for CO2 abatement was evaluated based on a case study for drying of distillers' spent grain.

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 score0.056
Threshold uncertainty score0.215

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 head0.014
GPT teacher head0.220
Teacher spread0.206 · 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