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Record W2011625744 · doi:10.1515/hf.2007.011

Kiln-drying lumber quality of hybrid poplar clones

2007· article· en· W2011625744 on OpenAlexafffundabout
Kyu‐Young Kang, Slobodan Bradic, Stavros Avramidis, Shawn D. Mansfield

Bibliographic record

VenueHolzforschung · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsUniversity of British Columbia
FundersNatural Resources CanadaUniversity of Arizona
KeywordsRaw materialKilnPulp and paper industryBioenergyContext (archaeology)Environmental scienceBiofuelEngineered woodShort rotation forestryGreen woodAgronomyWaste managementWood dryingWater contentBiologyEngineeringMaterials scienceComposite materialEcology

Abstract

fetched live from OpenAlex

Abstract Hybrid poplars are currently used in North America primarily for the production of pulp fibre and in the manufacture of engineered solid wood products. Recently, the deployment of poplars as a short-rotation fibre crop has been of interest to mitigate the increasing amount of plantation-grown short fibre resources (hardwoods) derived from the Southern Hemisphere, as well as in the context of global climate change, both as a means to rapidly sequester carbon and as a feedstock for potential bioenergy production. Knowledge on the utility of hybrid poplars in the value-added secondary wood-processing sector, however, is very limited. To improve this situation, the variation in kiln-drying quality of five hybrid poplar genotypes of similar age, harvested from a common site in British Columbia, Canada, was evaluated for three different kiln-drying schedules. The results clearly demonstrate that the drying schedule has a greater effect on grade recovery and the degree of deformation than the hybrid poplar genotype. Furthermore, it was shown that many of the deformations inherently associated with wood derived from fast-grown trees can be reduced or removed with drying, in particular with an aggressive drying schedule.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.034
GPT teacher head0.268
Teacher spread0.234 · 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 designBench or experimental
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

Citations16
Published2007
Admission routes3
Has abstractyes

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