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Record W3113067979 · doi:10.1139/cjfr-2020-0340

Detection of wood decay and cavities in living trees: a review

2020· review· en· W3113067979 on OpenAlexvenueno aff
Ayodele O. Soge, O. I. Popoola, Adedeji A. Adetoyinbo

Bibliographic record

VenueCanadian Journal of Forest Research · 2020
Typereview
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsTree healthTree (set theory)Environmental scienceAgroforestryComputer scienceEcologyBiologyMathematics

Abstract

fetched live from OpenAlex

It has been established that wood decay and cavities in tree stems contribute significantly to tree failures. Several techniques have been reported by researchers for detecting wood decay and cavities in living trees. These techniques are reviewed in this study under two broad categories: invasive and noninvasive methods. The invasive methods include traditional (decay detecting drill, increment borer, and boroscope), radiographic, acoustic, and electrical resistivity techniques. The noninvasive methods comprise microwave scanning, magnetic resonance imaging, X-ray tomography, and traditional techniques involving the use of mallets. Two or more methods are usually combined to investigate the health status of a tree for comparison and validation of results. The prospects and challenges of the various techniques in diagnosing wood decay, cavities, and other structural defects in living trees are reported. This review aims to help researchers in this field identify areas of further work towards the efficient monitoring and management of forest and urban trees.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.091
GPT teacher head0.324
Teacher spread0.233 · 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 designOther design
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

Citations51
Published2020
Admission routes1
Has abstractyes

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