MétaCan
Menu
Back to cohort
Record W7025331225

Using Landscape Approaches in National Biodiversity Strategy and Action Planning

2023· other· en· W7025331225 on OpenAlexaboutno aff

Bibliographic record

VenueUNU Collections (United Nations University) · 2023
Typeother
Languageen
FieldMedicine
TopicBiomedical and Chemical Research
Canadian institutionsnot available
Fundersnot available
KeywordsSeascapeBiodiversityDocumentationIndigenousAction (physics)Traditional knowledgeLandscape assessmentTransformative learningSustainability
DOInot available

Abstract

fetched live from OpenAlex

This publication explores the transformative potential of landscape approaches in biodiversity conservation, advocating for holistic strategies that reconcile diverse landscape and seascape uses. Emphasizing direct and indirect applications, it highlights the pivotal role of national governments, subnational authorities, indigenous communities, and private landowners. By fostering collaboration and establishing shared visions, stakeholders can create sustainable management plans, outlined within National Biodiversity Strategies and Action Plans (NBSAPs). The publication delves into the integration of landscape approaches into national conservation targets, as exemplified by the Kunming-Montreal Global Biodiversity Framework. It underscores the importance of proactive engagement, emphasizing meticulous monitoring and documentation of successes and failures, shared through national reports. Furthermore, the publication explores cross-sector plans and sector-specific strategies as effective channels for integrating landscape approaches, aligning conservation with diverse land and sea use activities. In essence, this guide champions a unified, adaptable, and inclusive approach, offering a roadmap towards harmonizing human activities with the preservation of biodiversity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.146
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.2120.142
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.261
GPT teacher head0.336
Teacher spread0.074 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueUNU Collections (United Nations University)Same topicBiomedical and Chemical ResearchFrench-language works237,207