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Record W2076939699 · doi:10.1139/l04-113

Beijing water resources and the south to north water diversion project

2005· article· en· W2076939699 on OpenAlexvenueno aff

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Resources and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsBeijingWater conservationWater resourcesWater scarcityWater resource managementIntegrated water resources managementWater supplyEnvironmental sciencePopulationSustainable developmentResource (disambiguation)Water diversionWater useChinaEnvironmental engineeringGeography

Abstract

fetched live from OpenAlex

Beijing is located in a semiarid region, and water shortage is a common problem in the city. Along with the rapid increase in water demand, due to fast socioeconomic development and an increase in population, a shortage of water resources and a deterioration of the water environment have become obstacles to sustainable socioeconomic development in Beijing. In the long run, sustainable water resources management, water conservation, and completion of the south to north water diversion project will solve the problem. This paper introduces the water resources situation in Beijing; analyzes future water demand; and discusses the actions of water saving, nontraditional water resources exploitation, wetland construction, and water environment protection. The paper also explains the importance of the south to north water diversion project and the general layout of the water supply strategy, water distribution system, and methods to efficiently use the diverted water in Beijing.Key words: water resources, water supply, water saving, water recycling, water diversion.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.000
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 head0.004
GPT teacher head0.153
Teacher spread0.149 · 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
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

Citations35
Published2005
Admission routes1
Has abstractyes

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