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Record W2353966809

Evaluation of Vulnerability to Drought in Hexi Oasis

2014· article· en· W2353966809 on OpenAlexaff
Yong Guo-zhen

Bibliographic record

VenueSoils · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Agricultural Sciences
Canadian institutionsScience North
Fundersnot available
KeywordsVulnerability (computing)UrbanizationGeographyAdaptive capacityNatural hazardNatural disasterSocial vulnerabilityWater resource managementEnvironmental scienceClimate changeEcologyPsychological resilienceMeteorologyBiologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

Using the entropy method and the model of contribution, the drought vulnerability and its major contribution factors in Hexi oasis were analyzed. The results showed that: the drought vulnerability in Zhangye City, Jiuquan City and Jinchang City were in the medium level, which in Jiayuguan City was in the low level and in Wuwei City was in very high level. The spatial differentiation of drought vulnerability in Hexi oasis was consistent with urbanization level, the sensitivity to drought was closely related with urbanization level, and the ability to cope with drought was affected by economic development and natural factors, but the former's effect was more than the latter. The main contribution factors were not the same in the index hierarchy of drought vulnerability among different cities, but shared generally a convergence trend, mainly in reflected in social drought sensitivity and response to drought, natural conditions, etc. Finally, corresponding countermeasures were put forward to drought vulnerability.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.261
Teacher spread0.241 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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