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Record W4392657766 · doi:10.3390/f15030513

Unearthing Current Knowledge Gaps in Our Understanding of Tree Stability: Review and Bibliometric Analysis

2024· article· en· W4392657766 on OpenAlex
Emmanuel Chukwudi Ekeoma, Mark Sterling, Nicole Metje, John Spink, Niall Farrelly, Owen Fenton

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueForests · 2024
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsWestern University
FundersTeagasc
KeywordsWindthrowClimate changeEnvironmental resource managementDiversification (marketing strategy)Forest managementGeographyEcological stabilityTree (set theory)AgroforestryEcologyForestryEcosystemEnvironmental scienceBusinessBiology

Abstract

fetched live from OpenAlex

Forest preservation and management are paramount for sustainable mitigation of climate change, timber production, and the economy. However, the potential of trees and forests to provide these benefits to the ecosystem is hampered by natural phenomena such as windthrow and anthropogenic activities. The aim of the current research was to undertake a critical thematic review (from 1983 to 2023) informed by a bibliometric analysis of existing literature on tree stability. The results revealed an increase in tree stability research between 2019 and 2022, with the USA, France, and Italy leading in research output, while Scotland and England notably demonstrated high research influence despite fewer publications. A keyword analysis showed that tree stability can be divided into four themes: tree species, architecture, anchorage, and environmental factors. Prominent studies on tree stability have focused on root anchorage. However, more recently, there has been a growing emphasis on urban forestry and disease-induced tree damage, underscoring a shift towards climate change and diversity research. It was concluded that considerable knowledge gaps still exist; that greater geographic diversification of research is needed and should include tropical and sub-tropical regions; that research relating to a wider range of soil types (and textures) should be conducted; and that a greater emphasis on large-scale physical modelling is required. Data and knowledge produced from these areas will improve our collective understanding of tree stability and therefore help decision makers and practitioners manage forestry resources in a more sustainable way into the future.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaBibliometrics
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.564
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0150.061
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.071
GPT teacher head0.327
Teacher spread0.256 · 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