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Record W2118295263 · doi:10.1038/nature02403

The worldwide leaf economics spectrum

2004· article· en· W2118295263 on OpenAlexaff
Ian J. Wright, Peter B. Reich, Mark Westoby, David D. Ackerly, Zdravko Baruch, Frans Bongers, Jeannine Cavender‐Bares, Terry Chapin, Johannes H. C. Cornelissen, Matthias Diemer, Jaume Flexas, Éric Garnier, Philip K. Groom, Javier Gulías, Kouki Hikosaka, Byron B. Lamont, Tali D. Lee, William Lee, Christopher H. Lusk, Jeremy J. Midgley, Marie‐Laure Navas, Ülo Niinemets, Jacek Oleksyn, Noriyuki Osada, Hendrik Poorter, Pieter Poot, Lynda D. Prior, V. I. P’yankov, Catherine Roumet, Sean C. Thomas, Mark G. Tjoelker, Erik J. Veneklaas, Rafael Villar

Bibliographic record

VenueNature · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicPlant Water Relations and Carbon Dynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiomeTraitSpecific leaf areaPlant functional typeLeaf sizeNutrientBiologyScale (ratio)EcologyVegetation (pathology)Environmental scienceBotanyPhotosynthesisEcosystemGeographyComputer scienceCartography

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0290.002

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 head0.002
GPT teacher head0.178
Teacher spread0.176 · 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 designObservational
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

Citations8,811
Published2004
Admission routes1
Has abstractno

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