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Record W1968290812 · doi:10.1139/x08-193

Visual identification, physical properties, ash composition, and water diffusion of wetwood in<i>Gmelina arborea</i>

2009· article· en· W1968290812 on OpenAlexaffvenue
Róger Moya, Freddy Muñoz, Dragica Jeremic, Alexánder Berrocal

Bibliographic record

VenueCanadian Journal of Forest Research · 2009
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of Toronto
FundersInstituto Tecnológico de Costa Rica
KeywordsGmelinaHorticultureChemistryBotanyWater contentComposition (language)MoistureBiologyGeology

Abstract

fetched live from OpenAlex

Wetwood is commonly reported in temperate species but not so in tropical species. In an old Gmelina arborea Roxb. plantation, wetwood was identified by a darker colour compared with the rest of heartwood; by a higher moisture content (average 182%); and a lower specific gravity (0.34, compared with 0.38 for sapwood and heartwood). Tangential shrinkage was 3.7%, which was significantly higher than that of heartwood and sapwood. Radial shrinkage was not significantly different between wetwood and sapwood, but it was significantly greater (2.6%) in wetwood than in heartwood (1.8%). Wetwood had a significantly higher pH than normal wood, but ash composition was similar to that of normal wood, with the exception of the amounts of iron and potassium. Wetwood and sapwood were less decay resistant than heartwood. Wetwood required less time than heartwood to reach equilibrium moisture content, but more time than sapwood. The tangential and longitudinal diffusion coefficients of wetwood were significantly higher than those of heartwood and lower than those of sapwood. In the radial direction sapwood showed a faster drying rate than wetwood but there was no significant difference between wetwood and heartwood.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.264
Teacher spread0.239 · 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

Citations18
Published2009
Admission routes2
Has abstractyes

Explore more

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