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Record W2341509470 · doi:10.14288/1.0108796

An investigation into the current and alternative methods for produce storage and transportation at the UBC Farm

2015· article· en· W2341509470 on OpenAlexaboutno aff
Stephan Bouthot, Rushat Agarwal, Tejbir Wason

Bibliographic record

VenuecIRcle (University of British Columbia) · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Manufacturing and Logistics Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsCurrent (fluid)Environmental scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

This report examines the economic costs of three produce transportation and storage methods for the UBC Farm in Vancouver, Canada. It looks in depth at the current storage method, the rubbermaid totes, as well as two potential replacements, corrugated cardboard boxes and burlap-lined totes. The report not only accounts for the direct monetary costs, but also for the opportunity cost for factors such as labour. Due to the approximations made for opportunity cost, this report may not be applicable to similar for-profit farms. The report conducts a thorough market research to inform the reader about the current practices in similar (small and big scale) operations. Cost prices are taken from prices published by other farm operation units in the greater Vancouver area. After comparing the three alternatives, this report concludes that burlap-lined rubber-maid totes are the most long term cost-effective option for the UBC Farm, while taking opportunity cost into account. The corrugated cardboard boxes save money on recurring costs due to labour, washing, and broken equipment but the cost of replacing the single-use boxes adds up over twenty years. The rubber-maid totes saved money due to its long lifespan, but the recurring costs and opportunity costs remains high. By modifying the existing system and adding a burlap-lining drastically reduces the washing cost and labour opportunity cost. This report recommends the UBC Farm modify their existing infrastructure and purchase burlap to line the plastic totes they already own. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.563
Threshold uncertainty score0.880

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0040.001
Scholarly communication0.0050.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.240
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2015
Admission routes1
Has abstractyes

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