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Record W4404612025 · doi:10.53555/sfs.v10i1.3191

The Environmental Sustainability of Edible Insects Farming- A study

2023· article· en· W4404612025 on OpenAlex
R. Basumatary

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.
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

VenueJournal of Survey in Fisheries Sciences · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Utilization and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityAgricultureAgroforestryBusinessGeographyEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

This study investigates the environmental sustainability of edible insect farming as an alternative to traditional livestock production. With the global population growing and concerns over the environmental impact of conventional agriculture, edible insects have emerged as a potential solution to food security and sustainability challenges. This research reviews the ecological benefits of insect farming, focusing on resource efficiency, reduced greenhouse gas emissions, and lower land and water usage compared to conventional meat production. The study also examines the challenges and barriers to scaling up insect farming, such as consumer acceptance, regulatory frameworks, and the need for further technological advancements. The findings suggest that, while insect farming offers a promising avenue for reducing the environmental footprint of food production, more comprehensive studies are needed to optimize production systems and fully assess long-term ecological impacts. This abstract summarizes key aspects of a study on edible insect farming's environmental sustainability, offering insights into its potential benefits and challenges.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.241

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.121
GPT teacher head0.268
Teacher spread0.147 · 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