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Record W4401301328 · doi:10.1007/978-3-031-29035-0_1

An Integrated Overview of the Water, Energy, Food Nexus in Central and South Asia

2024· book-chapter· en· W4401301328 on OpenAlexaff
Zafar Adeel, Benno Böer

Bibliographic record

VenueWater security in a new world · 2024
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNexus (standard)Water energyCentral asiaFood energyGeographyEnvironmental scienceWater resource managementPhysical geographyEngineeringBiology

Abstract

fetched live from OpenAlex

This chapter provides a description of the nexus between water, energy, and food security in the Central and South Asian region, including a description of the commonalities and differences. This description serves as the rationale for the regional footprint used in this book and the interactions between the countries including in the region. It provides an overview of the geopolitical considerations that make the region strategically important to the world. The following dynamic drivers of large-scale and strategic changes in the region are briefly discussed: geopolitical forces and events, trends related to urbanization, impacts of the global climate change, and emerging factors such as the COVID-19 global pandemic. A brief summary of the regional challenges and opportunities is provided, which serves as an introduction to the four sections of this book and various chapters: developmental and economic challenges; threats to water, energy, and food security; and political volatility. Finally, this chapter provides a section-by-section overview of the book as a whole.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0250.005

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 head0.020
GPT teacher head0.215
Teacher spread0.195 · 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 designTheoretical or conceptual
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

Citations1
Published2024
Admission routes1
Has abstractyes

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