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Record W4407447911 · doi:10.1126/science.adv8264

Time to fix the biodiversity leak

2025· article· en· W4407447911 on OpenAlexaff
Andrew Balmford, Thomas Ball, Ben Balmford, Ian J. Bateman, Graeme M. Buchanan, Gianluca Cerullo, Francisco d’Albertas, Alison Eyres, Ben Filewod, Brendan Fisher, Jonathan Green, Kyle S. Hemes, J. M. Holland, Miranda Lam, Robin Naidoo, Alexander Pfaff, Taylor H. Ricketts, Fiona J. Sanderson, Timothy D. Searchinger, Bernardo B. N. Strassburg, Thomas Swinfield, David Williams

Bibliographic record

VenueScience · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsCanadian Forest Service
FundersNatural Environment Research CouncilUK Energy Research CentreSight Research UKStrong
KeywordsBiodiversityLeakBiodiversity conservationBusinessEnvironmental planningEnvironmental scienceEnvironmental resource managementBiologyEcologyEnvironmental engineering

Abstract

fetched live from OpenAlex

The risk that locally successful nature conservation may be shifting problems elsewhere can no longer be ignored.

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)0.005
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.100
Threshold uncertainty score0.334

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0050.003
Scholarly communication0.0070.012
Open science0.0020.007
Research integrity0.0100.016
Insufficient payload (model declined to judge)0.1000.035

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 head0.005
GPT teacher head0.189
Teacher spread0.184 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations32
Published2025
Admission routes1
Has abstractyes

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