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Record W4387065124 · doi:10.54406/jnpr.2023.14.1.075

The Review on the Global Status of Other Effective Conservation Measures for Kunming-Montreal Global Biodiversity Framework Target 3

2023· article· en· W4387065124 on OpenAlexaboutno aff
Sunjoo Park, Hag Young Heo

Bibliographic record

VenueKorea National Park Research Institute · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEcology and Conservation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityCorporate governanceEnvironmental resource managementBusinessHabitatBiodiversity conservationEcosystem servicesGeographyEcosystemEnvironmental planningEcologyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

With the adoption of Kunming-Montreal Global Biodiversity Framework, Other Effective Conservation Measures are considered important instruments to achieve the 30 by 30 target. This study reviewed the characteristics of 829 OECMs sites through identifying the related instruments and the conservation outcomes using World Database of OECMs. OECMs, reported from 9 countries, covered approximately 1% of global terrestrial and 0.1% of marine areas. OECMs were governed and managed by law, planning, contract and the way of customary management. OECMs have contributed to biodiversity through conserving important ecological habitats and enhancing the connectivity, and promoting the related ecosystem services for local residents. In respect to governance types, proportion of shared governance was higher than that in protected areas.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.007
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.147
GPT teacher head0.380
Teacher spread0.233 · 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 designSystematic review
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

Citations1
Published2023
Admission routes1
Has abstractyes

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