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Record W4410404230 · doi:10.17520/biods.2024593

China’s implementation model of international environmental conventions and its application to the Convention on Biological Diversity—Achieving the Kunming-Montreal Global Biodiversity Framework targets and the role of national parks

2025· article· en· W4410404230 on OpenAlexaboutno aff
Tian Zhiqi, Yang Su

Bibliographic record

VenueBiodiversity Science · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicInternational Maritime Law Issues
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsConvention on Biological DiversityBiodiversityChinaDiversity (politics)Environmental resource managementConventionEnvironmental planningEnvironmental protectionPolitical scienceGeographyEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

摘要: 从全球来看, 完成《生物多样性公约》等国际公约的履约目标存在共性难点, 但中国履约模式易于克服难点: 中央在 决策层面判断"大事"、集中力量, 并通过规划、考核、资金三方面主导手段将力量层层传导到执行层面, 使国际公约目标转 化为有执行保障机制的国家任务, 这在将《联合国气候变化框架公约》国际目标转化为中国的"双碳"

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)0.006
metaresearch head score (Gemma)0.005
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: Empirical · Consensus signal: none
Teacher disagreement score0.309
Threshold uncertainty score0.614

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0040.004
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0030.003
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 head0.009
GPT teacher head0.246
Teacher spread0.237 · 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
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
Published2025
Admission routes1
Has abstractyes

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