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Record W2060923425 · doi:10.5539/ass.v6n10p44

Analysis and Evaluation of Taiwan Water Shortage Factors and Solution Strategies

2010· article· en· W2060923425 on OpenAlexvenueno aff
Ching‐Yu Wang, Jhen-Bin Wang

Bibliographic record

VenueAsian Social Science · 2010
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsnot available
Fundersnot available
KeywordsWater scarcityWater conservationWater resourcesWater resource managementBusinessEnvironmental scienceNatural resourceNatural resource economicsEnvironmental planningEnvironmental resource managementEconomicsEcology

Abstract

fetched live from OpenAlex

Water resources are precious but limited natural possessions and significant to people’s livings. If the water resources could not be allocated well, the related problems will grow. The water shortage problems are not only related to rainfall, geographic landform, climate, populations, and economic activities, but also allocation, supply, and management of water resources. Hence, water shortage has become an important issue in our country.This study aims to discuss the factors of water shortage from the viewpoints of political-economics, nature, and management. Natural factors cover special geographic structure, geological structure, and climate change. Management factors include sediment deposit, water turbidity, soil conservation, water nutrition, pipeline leaking, water pollution, water waste, and water organizations. From the management perspective, the importance of water shortage factors is assessed to understanding the critical factors. The analytic hierarchy process was used to evaluate the water shortage factors to promote the rationalization of strategy formulation. The results show that higher important facts are water waste, soil conservation, and pipeline leaking.

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 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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.134

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 head0.013
GPT teacher head0.246
Teacher spread0.234 · 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 teacher head, 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

Citations8
Published2010
Admission routes1
Has abstractyes

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