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Record W6884619606 · doi:10.11575/prism/38275

Alternative Solutions for Fruit and Vegetable Price Look-Up Stickers Generating Waste in the Environment

2020· other· en· W6884619606 on OpenAlexaboutno aff

Bibliographic record

VenueOpen MIND · 2020
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPosition (finance)Sustainable productsWaste disposalMunicipal solid wasteSustainabilityHousehold waste

Abstract

fetched live from OpenAlex

Waste generation impacts the environment, energy, economy, and society. Price Look-Up stickers used on the fresh produce become environment litter, can cause compost contamination, and contribute to climate change. This research was conducted to identify alternative and sustainable solutions for Price Look-Up stickers. Two surveys were conducted for the purpose of this research. Survey I was geared towards identifying the potential for adoption of alternative solutions among produce processors and distributors . Survey II was intended for analysing sticker waste disposal practices and attitudes among end consumers. Representatives from the sticker manufacturing industry were interviewed to gain information for analysing the prospects for innovation, availability, and adoption of alternative solutions. I consulted with officials at the Canadian Produce Marketing Association to understand their position on need for alternatives. Findings from the surveys and industry consultations were used to develop recommendations for The City of Calgary.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.056
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0560.006

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 head0.061
GPT teacher head0.293
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 source (direct Gemma or distilled Codex), not a consensus.

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

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
Published2020
Admission routes1
Has abstractyes

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