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Record W1818842839 · doi:10.1079/9781845931728.0211

Energy-irrigation nexus in South Asia: improving groundwater conservation and power sector viability.

2007· preprint· en· W1818842839 on OpenAlexaff
Tushaar Shah, Christopher A. Scott, Avinash Kishore, Abhishek Sharma

Bibliographic record

VenueCABI eBooks · 2007
Typepreprint
Languageen
FieldEnvironmental Science
TopicWater-Energy-Food Nexus Studies
Canadian institutionsPricewaterhouseCoopers (Canada)
FundersConsortium of International Agricultural Research Centers
KeywordsNexus (standard)Water-energy nexusIrrigationWater resource managementGroundwaterEnvironmental scienceNatural resource economicsBusinessEconomicsGeologyEngineeringEcologyGeotechnical engineering

Abstract

fetched live from OpenAlex

In the highly populated South Asian region, where pump irrigation has gained predominance over gravity-flow irrigation in recent decades, the fortunes of groundwater and energy economies are closely tied. Little can be done in the groundwater economy that will not affect the energy economy, and the struggle to make the energy economy viable is frustrated by the often violent opposition from the farming community to the rationalization of energy prices. As a result, the region's groundwater economy has boomed at the expense of the development of the energy economy. This report suggests that this does not have to be so; and the first step to evolving approaches to sustaining a prosperous groundwater economy with a viable power sector is for the decision makers in the two sectors to talk to each other, and jointly explore better options for energy-groundwater co-management which, the authors suggest, have so far been overlooked.

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)0.001
metaresearch head score (Gemma)0.002
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: Other · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.208
Teacher spread0.192 · 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
GenreOther

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

Citations82
Published2007
Admission routes1
Has abstractyes

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