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Record W2003551191 · doi:10.1300/j030v12n04_04

Financial Feasibility of Producing Value-Added Seafood from Shrimp Waste in Quebec

2003· article· en· W2003551191 on OpenAlexaffabout
Peter Goldsmith, F. Amankwah, Kisan Gunjal, James P. Smith

Bibliographic record

VenueJournal of Aquatic Food Product Technology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsMcGill University
Fundersnot available
KeywordsInternal rate of returnPayback periodShrimpNet present valueCash flowPresent valueInvestment (military)Rate of returnReturn on investmentBusinessAgricultural scienceBenefit–cost ratioAgricultural economicsDiscounted cash flowFisheryEnvironmental scienceFinanceEconomicsProduction (economics)Biology

Abstract

fetched live from OpenAlex

Shrimp waste disposal represents a financial and environmental cost to processors and society. There have been successful biotechnology experiments in producing certain value-added marketable consumer products from shrimp waste. This study reports on the economics of that process and its commercial viability in Quebec. Discounted cash flow methods (NPV, IRR) and the payback period criteria were employed to conduct investment analysis in a technology that transforms shrimp processing waste into value-added surimi-shrimp nuggets.The planned extension was estimated to cost $4.3 M in capital investments and can process an estimated 5,000 mt of shrimp nuggets per year at $2.62/kg. If the plant operates at full capacity (5,400 hours per year) for 10 years, it will recover initial outlay and interest payments in 2.3 years with a net present value of $6.9 M and an internal rate of return of 43%. The expected values of net present value, internal rate of return and the payback period for the project, given varying output levels, were $3.27 M, 26% and 3.9 years, respectively.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.023
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.245
Teacher spread0.232 · 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 designBench or experimental
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

Citations2
Published2003
Admission routes2
Has abstractyes

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