MétaCan
Menu
Back to cohort
Record W4401301276 · doi:10.1007/978-3-031-29035-0_3

Water-Food Equation in Central and South Asia

2024· book-chapter· en· W4401301276 on OpenAlexaff
Manzoor Qadir

Bibliographic record

VenueWater security in a new world · 2024
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsUnited Nations University Institute for Water, Environment, and Health
Fundersnot available
KeywordsCentral asiaEnvironmental scienceGeographyPhysical geography

Abstract

fetched live from OpenAlex

Population growth and urbanization converge upon the Central and South Asia region, where water demand is expected to continue rising in order to support food production systems. In contrast, some freshwater resources are likely to be diverted from agriculture to provide water for other increasing demands, such as municipal and industrial activities. In such a context, achieving water and food security has become an entangled challenge in the region where most countries are net importers of major cereals. Ensuring both sides of the water-food equation complement each other needs insights into strategies that promote efficient use of available water resources to support efforts in achieving food security across the region. The following aspects of water resources management are needed in building a water- and food-secure future in the region by (1) promoting water conservation, water recycling and reuse; (2) ensuring sustainable water resources augmentation; (3) supporting productivity enhancement of underperforming land and water resources; and (4) addressing challenges beyond technical solutions accompanied by a call for sustainable intensification of agricultural production systems. Policymakers and water professionals need to recognize and treat water as a highly valuable precious resource for sustainable agricultural production systems and a cornerstone of the circular economy. The key to support efforts in ensuring water- and food-security in the Central and South Asia regions include pertinent political agendas and associated public policies, supportive institutions, strengthening institutional collaborations, and skilled professionals.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0020.003
Open science0.0000.002
Research integrity0.0010.002
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 head0.018
GPT teacher head0.198
Teacher spread0.181 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueWater security in a new worldSame topicWater-Energy-Food Nexus StudiesFrench-language works237,207