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Record W4406853173 · doi:10.1016/j.isci.2025.111902

Catalyzing sustainable development goals through the water-energy-food nexus

2025· review· en· W4406853173 on OpenAlexaff
Luxon Nhamo, Sylvester Mpandeli, Stanley Liphadzi, Tafadzwanashe Mabhaudhi

Bibliographic record

VenueiScience · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsUnited Nations University Institute for Water, Environment, and Health
FundersWater Research CommissionWellcome Trust
KeywordsNexus (standard)Water energySustainable developmentNatural resource economicsEnvironmental scienceBusinessEnvironmental protectionEnvironmental ethicsChemistryEcologyEngineeringEconomicsBiology

Abstract

fetched live from OpenAlex

Water, energy, and food (WEF) are central to sustainable development as they are vital for socio-ecological and socio-economic sustainability and human and environmental wellbeing. How the three are used and managed is central to either the aggravation of climate change or the enhancement of resilience and adaptation strategies. This mixed transdisciplinary study developed a WEF nexus-based framework to guide strategic policy decisions to catalyze progress toward achieving sustainable development goals. The aim is to guide the cross-sectoral management of resources for sustainable development under climate change, increasing demand, depletion, degradation, and uncertainty. Past and present data on resource management was assessed to comprehend future availability toward achieving sustainable development outcomes for people and the planet. The fundamentals of holistic WEF resources management were assessed, highlighting the significance of transformative, cross-sectoral, and circular approaches in enhancing resource use efficiency and sustainability. This is critical for informing sustainable natural resources management decisions.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0030.005
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 head0.028
GPT teacher head0.266
Teacher spread0.238 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations15
Published2025
Admission routes1
Has abstractyes

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