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Record W2063292842 · doi:10.1890/080116

The role of plantations in managing the world's forests in the Anthropocene

2009· review· en· W2063292842 on OpenAlexaff
Alain Paquette, Christian Messier

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2009
Typereview
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsEcoforestryEcosystem servicesTree plantingAnthropoceneAgroforestryEcosystemVariety (cybernetics)Forest ecologyEnvironmental resource managementNatural resource economicsBusinessGeographyEcologyEnvironmental scienceIntact forest landscapeEconomicsComputer science

Abstract

fetched live from OpenAlex

The public view of tree plantations is somewhat ambiguous. While planting a single tree is generally considered good for the environment, planting a million trees raises concerns in some circles. Although plantations are often used to compensate for bad forestry practices, to willingly simplify otherwise complex forest ecosystems, or as a strategy for allowing the current petroleum‐based economy to continue on its course, we believe plantations have a legitimate place in the sustainable management of forests. Multi‐purpose plantations, designed to meet a wide variety of social, economic, and environmental objectives, can provide key ecosystem services, help preserve the world's remaining primary forests, and sequester an important proportion of the atmospheric carbon released by humans over the past 300 years.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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
GenreReview

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

Citations564
Published2009
Admission routes1
Has abstractyes

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