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Record W2038854091 · doi:10.5539/jsd.v2n2p38

Current Status of Environmental Protection Measures in China

2009· article· en· W2038854091 on OpenAlexvenueno aff
Chao Liu, Shenggao Cheng

Bibliographic record

VenueJournal of Sustainable Development · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Quality and Pollution
Canadian institutionsnot available
Fundersnot available
KeywordsThrivingChinaEnvironmental planningBusinessEnvironmental resource managementEnvironmental pollutionEnvironmental protectionEnvironmental economicsRisk analysis (engineering)Political scienceEnvironmental scienceSociologyEconomics

Abstract

fetched live from OpenAlex

Human activities affect the environment more or less negatively due to thriving engineering constructions such as resources exploitation, municipal projects and so on. It is encouraging that, by applying some environmental protection measures to decrease pollution in cities and prevent disturbance from geo-environment due to constructions, have made big progress for the present. However, it is far from our utmost expect of environment protection. The inherent complexity and varied nature of geo-environment challenge policy makers how to assess the active effectiveness of environmental protection in scientific approaches., This paper, starting from antecedents achievements in China, outlined the present situation of environment protection in China, and featured the types and purposes of 21st century environmental sures in terms of their natures and functions, thereby comprehensively proposed research respective. Research conclusions were included: 1) the awareness to environmental protection measures is increasing and it present higher growth rate in 2006 and 2007 in terms of analyzing publications focused on environment protection; 2)

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)0.002
metaresearch head score (Gemma)0.003
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: Review · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.229
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 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
GenreReview

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

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