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Record W4281717750 · doi:10.1126/science.abl8974

Functional connectivity of the world’s protected areas

2022· article· en· W4281717750 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

VenueScience · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife-Road Interactions and Conservation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiodiversityLandscape connectivityEnvironmental resource managementFunctional connectivityGeographyWildlife corridorEnvironmental planningEcologyEnvironmental scienceBiologyWildlifeNeuroscience

Abstract

fetched live from OpenAlex

Global policies call for connecting protected areas (PAs) to conserve the flow of animals and genes across changing landscapes, yet whether global PA networks currently support animal movement-and where connectivity conservation is most critical-remain largely unknown. In this study, we map the functional connectivity of the world's terrestrial PAs and quantify national PA connectivity through the lens of moving mammals. We find that mitigating the human footprint may improve connectivity more than adding new PAs, although both strategies together maximize benefits. The most globally important areas of concentrated mammal movement remain unprotected, with 71% of these overlapping with global biodiversity priority areas and 6% occurring on land with moderate to high human modification. Conservation and restoration of critical connectivity areas could safeguard PA connectivity while supporting other global conservation priorities.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.382
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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