MétaCan
Menu
Back to cohort
Record W4402127615 · doi:10.1016/j.oneear.2024.08.003

Urgent climate action is needed to ensure effectiveness of protected areas for biodiversity benefits

2024· article· en· W4402127615 on OpenAlexaff
Akira Mori, Andrew Gonzalez, Rupert Seidl, Peter B. Reich, Laura E. Dee, Haruka Ohashi, Yann Hautier, Michel Loreau, Forest Isbell

Bibliographic record

VenueOne Earth · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsMcGill University
FundersHorizon 2020 Framework ProgrammeNational Academy of SciencesLaboratoire d'Excellence TULIPIchimura Foundation of New TechnologyH2020 European Research CouncilJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and TechnologyEuropean Research CouncilNational Science Foundation
KeywordsBiodiversityAction (physics)Environmental resource managementClimate changeEnvironmental planningBiodiversity conservationBusinessEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

Publisher of over 50 scientific journals across the life, physical, earth, and health sciences, both independently and in partnership with scientific societies including Cell, Neuron, Immunity, Current Biology, AJHG, and the Trends Journals.

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)0.024
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: Empirical · Consensus signal: none
Teacher disagreement score0.040
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0400.010

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 head0.123
GPT teacher head0.229
Teacher spread0.106 · 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
GenreEmpirical

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

Citations10
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueOne EarthSame topicEconomic and Environmental ValuationFrench-language works237,207