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Say No to the Thirsty Planet: Too Few Freshwater for the Daily Life of Human Beings

2018· article· en· W2883316831 on OpenAlexaboutno aff
Tao Hu, Changwei Pang

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Resources and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsChinaPer capitaNatural resource economicsResource (disambiguation)Quarter (Canadian coin)PopulationWater resourcesCarrying capacityGeographyFresh waterBusinessEnvironmental scienceWater resource managementEcologyEconomicsDemographyBiologyComputer scienceSociology

Abstract

fetched live from OpenAlex

Though more than 70 percent of the earth space is covered by ocean, only no more than 2.5 percent of the freshwater is available for the daily life of human beings. However, as the country who owns the biggest population in the world, China's per- capita average of freshwater resources amounts to only quarter of the world's. By analyzing the relationship between supply and demand of water resource, we build the Water Resources Carrying Capacity (WRCC) model and analyze the current situations of water resource in China.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.205
Teacher spread0.195 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations3
Published2018
Admission routes1
Has abstractyes

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