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Record W4409590251 · doi:10.1111/2041-210x.70035

Correction to ‘Forest and Biodiversity 2: A tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long‐term ecosystem function and resilience’

2025· article· en· W4409590251 on OpenAlexaboutno aff

Bibliographic record

VenueMethods in Ecology and Evolution · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityResilience (materials science)Diversity (politics)Term (time)EcosystemEnvironmental resource managementEcologyFunction (biology)GeographyPsychological resilienceSpecies diversityTree (set theory)Beta diversityEcosystem servicesForest ecologyEnvironmental scienceBiologyPsychologyMathematicsSociology

Abstract

fetched live from OpenAlex

Cavender-Bares, J., Grossman, J. J., Guzmán Q., J. A., Hobbie, S. E., Kaproth, M. A., Kothari, S., Lapadat, C. N., Montgomery, R. A., & Park, M. (2024). Forest and Biodiversity 2: A tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience. Methods in Ecology and Evolution, 15, 2400–2414. https://doi.org/10.1111/2041-210X.14435 In the paper by Cavender-Bares et al. (2024), it was incorrectly stated that the FAB2 tree diversity experiment was the largest of its kind in North America. It is the largest of the IDENT (International Diversity Experiment Network with Trees) experiments in North America. The BiodiversiTREE@SERC and BiodiversiTREE@SCBI experiments in Maryland and Virginia, USA, respectively, and the newly established University of Alberta long-term tree diversity experiment in Alberta, Canada each have larger total extents. We apologize for this error.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.034
GPT teacher head0.304
Teacher spread0.270 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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