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Record W3198006517 · doi:10.1016/j.gfs.2021.100574

Global overview of locusts as food, feed and other uses

2021· article· en· W3198006517 on OpenAlexfundno aff
James P. Egonyu, Sevgan Subramanian, Chrysantus M. Tanga, Thomas Dubois, Sunday Ekesi, Segenet Kelemu

Bibliographic record

VenueGlobal Food Security · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Utilization and Effects
Canadian institutionsnot available
FundersAustralian Centre for International Agricultural ResearchDirektoratet for UtviklingssamarbeidStyrelsen för Internationellt UtvecklingssamarbeteDirektion für Entwicklung und ZusammenarbeitInternational Development Research CentreRockefeller Foundation
KeywordsLocustCompromiseFood securityBusinessFood safetyBiologyNatural resource economicsAgricultureEcologyEconomicsFood science

Abstract

fetched live from OpenAlex

The term 'locusts' refers to insect species which can aggregate into migratory swarms that cause wide-scale destruction of crops and pasture, causing significant effect to food security. This review assesses the potential of harnessing locust swarms for beneficial uses. Among 21 known locusts, ~10 species have been traditionally consumed by humans or fed to animals for millennia in 65 countries. Their nutritional composition is comparable or superior to that of conventional meat. However, insecticide residues, microbial contaminants and allergens may compromise their safety. Some countries have developed regulations on edible insects , locusts inclusive. Safe and efficient harvest of locusts could offer nutritional and revenue opportunities in many developing countries and serve as a more sustainable management method than the widespread use of insecticides.

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.036
GPT teacher head0.275
Teacher spread0.239 · 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

Citations63
Published2021
Admission routes1
Has abstractyes

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