MétaCan
Menu
Back to cohort

Environment Geophysics on Environmental protection in China

2009· article· en· W1751977091 on OpenAlexvenueno aff
Jin Yang, Ye-xun Cheng, Zhao Zhangyuan, Ya-xin Yang

Bibliographic record

VenueAdvances in natural science/Advances in natural sciences · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicRemote Sensing and Land Use
Canadian institutionsnot available
Fundersnot available
KeywordsHarmChinaSustainable developmentDesertificationEnvironmental pollutionEnvironmental planningNatural resource economicsPollutionNatural (archaeology)Flood mythNatural resourceEnvironmental protectionBusinessEnvironmental resource managementEnvironmental scienceGeographyPolitical scienceEcologyEconomicsLaw

Abstract

fetched live from OpenAlex

The environmental problem conexists with the birth and development of human being. When people entered on the Industrial Revolution, especially the twentieth century, with the rapid improvement of the productivity level, the natural resources has been exploited and used at the unprecedented level. When people are creating the material wealth, they are also producing more and more pollution. The environmental problem has been more and more serious. This problem has already done harm to the human existence directly. In recent 20 years, the environmental problem has been one of the most important problems that people are concerned with. In China, there are also many environmental problems such as air pollution, water pollution, refuse treatment, desertification, sand calamity, soil erosion, drought, flood, biodiversity damage,and so on. Some of these problems have already affected the development of national economy and the living of people. So using the modern technology, uniting different subjects, studying these problems roundly and systematacially, and harnessing the pollution are important to the sustainable development of the society and economy. Key words: Geophysics; Environmental protection; pollution

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0000.005
Open science0.0010.000
Research integrity0.0000.001
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 head0.004
GPT teacher head0.222
Teacher spread0.217 · 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.

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

Citations0
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in natural science/Advances in natural sciencesSame topicRemote Sensing and Land UseFrench-language works237,207