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Record W2163816029 · doi:10.1017/s1355770x05002743

Spatially correlated rainfall in a protective irrigation system

2006· article· en· W2163816029 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironment and Development Economics · 2006
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsAcadia University
Fundersnot available
KeywordsStylized factIrrigationVolatility (finance)EconomicsDeficit irrigationEnvironmental scienceWater supplyAgricultural economicsEconometricsIrrigation managementEcology

Abstract

fetched live from OpenAlex

Allowing water to be traded in an irrigation system with de facto riparian rights can increase the efficiency of water use. With irrigation supplementing uncertain rainfall, both supply and demand for water are uncertain. When rainfall events are positively correlated, water supply and demand movements are negatively correlated, causing large price fluctuations. Using a stylized two crop, two region irrigation system, numerical integration over a bivariate rainfall distribution is used to demonstrate the impact of varying rainfall correlation on water price, expected returns, and return variability. A spot market for water captures the majority of the returns to water rights transfers, relative to a complete market. This spot market results in higher returns and reduced return volatility for farmers in the water deficit region, while farmers in the water surplus region see greater returns but also greater return volatility.

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.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.003
GPT teacher head0.120
Teacher spread0.117 · 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