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Record W2016739309 · doi:10.1002/ird.555

Irrigation in the context of today's global food crisis

2010· article· en· W2016739309 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

VenueIrrigation and Drainage · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture, Water, and Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsFood securityFood pricesContext (archaeology)Agricultural economicsBusinessPopulationWater scarcityAgricultureEconomicsNatural resource economicsGeography

Abstract

fetched live from OpenAlex

Abstract During 2008 the world witnessed a global food crisis which caused social unrest in many countries and drove 75 million more people into poverty. The crisis resulted from sharply higher oil prices, increased bio‐fuel production, dwindling grain stocks, market speculation, changing food consumption patterns in emerging economies, and changes in world trade agreements, among other factors. Although the rise in food prices was sudden, the fragility of global food security had been developing for years. During the 1960s and 1970s food production kept pace with demand as more cropland was irrigated and yields of irrigated crops increased dramatically. Irrigation played a critical role in combating hunger, poverty and death due to malnutrition. However, the environmental and social consequences of large irrigation schemes came into question, and investments in irrigation subsequently diminished. Today's food crisis is compounded by a rapidly growing world population, the conversion of food producing lands to bio‐fuel production, diminishing available freshwater supplies, competition for water by other sectors, climate change impacts, and the reduction in arable lands due to urbanization. It is critical that investments focus on increasing agricultural production through improved management of land and water resources, and the involvement of all stakeholders. Copyright © 2010 John Wiley & Sons, Ltd.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.591
Threshold uncertainty score0.301

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 head0.009
GPT teacher head0.240
Teacher spread0.230 · 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