MétaCan
Menu
Back to cohort
Record W2379805159

Preliminary Assessment on Pressure and Threat of Protected Area in Northeast China

2011· article· en· W2379805159 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicQ Methodology Applications
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsPoachingProtected areaDeforestation (computer science)TourismPrioritizationChinaCommissionBusinessEnvironmental planningEnvironmental resource managementEnvironmental protectionGeographyWildlifeEnvironmental scienceEcology
DOInot available

Abstract

fetched live from OpenAlex

The methodology of Rapid Assessment and Prioritization of Protected Areas Management(RAPPAM) recommended by World Commission on Protected Areas(WCPA) and World Wide Fund for Nature(WWF) was used in investigating and analyzing pressures,threats and trends of the protected areas in Northeast China.The results showed that the following six factors had broader sphere of influence,affecting at higher degree and lasting a longer time in the 14 threatening factors: fires,deforestation,poaching,non-timber forest products(NTFP),tourism and grazing.Protected areas should focus on control of these threatening factors.Therefore,the future management of protected areas should strengthen monitoring of fires,deforestation,poaching,NTFP,etc.Meanwhile,protected areas should develop relevant policies and take appropriate measures to effectively control and reduce the negative impact of eco-tourism to improve the effectiveness of management.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.066
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.282
GPT teacher head0.436
Teacher spread0.154 · 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

Quick stats

Citations3
Published2011
Admission routes1
Has abstractyes

Explore more

Same topicQ Methodology ApplicationsFrench-language works237,207