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Record W4386698833 · doi:10.3389/fsufs.2023.1188467

The future of protein sources in livestock feeds: implications for sustainability and food safety

2023· article· en· W4386698833 on OpenAlexfundno aff
Georgios Pexas, Bob Doherty, I. Kyriazakis

Bibliographic record

VenueFrontiers in Sustainable Food Systems · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsnot available
FundersEconomic and Social Research CouncilQueen's UniversityQueen's University BelfastFood Standards Agency
KeywordsLivestockFood securitySustainabilityBusinessFood industryCompetition (biology)Production (economics)Food systemsNatural resource economicsEnvironmental resource managementAgricultureEconomicsEcologyBiologyFood science

Abstract

fetched live from OpenAlex

The feed-food competition for environmental and economic resources raises increasing concerns about the production and supply of protein for the global livestock sector. Risks to food-security and approaching deadlines for global sustainable development, means exploring alternative protein feed ingredients is imperative. This Review discusses the potential for soilless, local and circular protein feed sources to provide solutions for key sustainability and food-security threats to the global livestock sector, through their partial incorporation in future livestock feeds and feeding systems. In doing so, it offers a holistic insight into the potential opportunities, but also risks associated with such alternatives. Through this analysis, a four-point strategic plan is synthesized to facilitate higher-level policy making that may enable implementation of these alternative ingredients at commercial scales, building toward a more sustainable and resilient livestock industry.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.392
Threshold uncertainty score0.716

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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 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

Citations62
Published2023
Admission routes1
Has abstractyes

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