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Record W7110461848

Niet alleen natuur: in bos groeit hout : Pleidooi voor een herwaardering van houtoogst in Nederlandse bossen

2025· other· nl· W7110461848 on OpenAlexaff

Bibliographic record

VenueSocio-Environmental Systems Modeling · 2025
Typeother
Languagenl
Field
Topic
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsDeforestation (computer science)BiodiversityResource (disambiguation)Sustainable forest managementForest managementWood productionProduction (economics)Provisioning
DOInot available

Abstract

fetched live from OpenAlex

Dutch forests, despite their small size, play a crucial role in biodiversity onservation, recreation, and carbon cycling. However, their role in the provisioning of wood is increasingly disregarded or even rejected.This essay advocates a renewed appreciation of sustainable wood harvesting as a key resource for the bioeconomy. Wood harvest in the Netherlands has declined by 25% in the past decade due to complex regulations and negative perceptions. Yet, the demand for wood is rising. Misconceptions equating wood harvesting with deforestation or destruction of nature hinder balanced forest management. In reality, responsible harvesting can contribute to carbon mitigation and nature conservation. Historically, Dutch forests have been shaped by human intervention, and continued forest management - including wood harvest - can enhance both ecological and economicbenefits. Rather than relying almost exclusively onimports, the Netherlands should integrate sustainablewood production into its forest policy, ensuring amultifunctional approach that balances conservation,recreation, and resource use.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.541
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0040.019

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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
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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