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Record W2793574801 · doi:10.7451/cbe.2017.59.8.23

Techno-economic evaluation of microwave drying of wheat distiller’s grain with solubles in Saskatchewan.

2017· article· en· W2793574801 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.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueCanadian Biosystems Engineering · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Drying and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsMicrowaveEnvironmental scienceAgricultural engineeringAgronomyMaterials sciencePulp and paper industryAgricultural economicsEconomicsEngineeringBiology

Abstract

fetched live from OpenAlex

The incorporation of microwave drying system in industry-scale drying of wet wheat distillers grain with solubles (WDGS) was evaluated foreconomic viability under three scenarios: (i) microwave drying, where only microwave energy was used in reducing WDGS from 70% to 10% moisture on wet basis (w.b.); (ii) booster drying, where microwave energy was applied after rotary drying when drying rates began to fall; and (iii) finish drying, where microwave drying was used near the end of the drying process. Complete replacement of the conventional hot air drying system with microwave energy was not economically feasible under the present set of assumptions. Although energy requirement during microwave drying was substantially lower than that of rotary drying, the cost of electricity in providing the microwave energy was seen as a major hindrance. Lower electricity rates, availability of cheaper power sources, and attractive market incentives, such as premium prices for high protein quality wheat DDGS, may be necessary to encourage ethanol producers to invest in the technology. Finish drying, which used the least amount of electrical energy among the three scenarios, was seen as the more economically viable option. Costs associated with the other DDGS production processes also have to be assessed to have a more comprehensive picture of the costs and the benefits of investing on microwave drying technology for protein quality improvement.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.206
Teacher spread0.183 · 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