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Record W2099531320 · doi:10.21083/surg.v4i2.1200

Brewery resource and energy recovery system

2011· article· en· W2099531320 on OpenAlexaffvenueabout
Kathryn Loog, Randi Phinney, Krista Read, Laura Robertson

Bibliographic record

VenueSURG Journal · 2011
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPayback periodTariffCapital costNet present valueElectricityWaste managementEnvironmental scienceEffluentNatural gasBiogasBusinessEnvironmental engineeringEngineeringProduction (economics)Economics

Abstract

fetched live from OpenAlex

In this paper, a bio-gas and spent grain utilization system for a brewery is presented. The bio-gas component of the system consists of a generator to produce electricity for sale through the Feed-In Tariff program offered by the Ontario Power Authority. The spent grain component consists of a gasification system to produce syngas, which will reduce the natural gas requirements of the facility. A membrane bioreactor will be used downstream of the current anaerobic digester in order to eliminate the municipal surcharges on the effluent water and allow for water recycling. The design was analyzed using a net present value (NPV) analysis. The results showed a capital cost of $8.9 million for the overall system, a payback period of 8 years, and a 20-year NPV of $24 million. Recommendations are made as to how the economic and environmental benefits to the brewery could be improved.

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.

How this classification was reachedexpand

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.212

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 head0.012
GPT teacher head0.156
Teacher spread0.144 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2011
Admission routes3
Has abstractyes

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