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Record W1566141049 · doi:10.15376/biores.6.4.4696-4704

Evaluation of decay resistance for steam-heat-treated wood

2011· article· en· W1566141049 on OpenAlexaff
Yongjian Cao, Jianxiong Lu, Rongfeng Huang, Youke Zhao, Yuzhang Wu

Bibliographic record

VenueBioResources · 2011
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of New Brunswick
FundersNational Natural Science Foundation of China
KeywordsHorticultureMaterials sciencePulp and paper industryAnimal scienceChemistryBotanyBiology

Abstract

fetched live from OpenAlex

The objective of this research was to evaluate the influence of steam-heat treatment on the decay resistance of Chinese white poplar and Chinese fir wood against the wood-rotting fungi Gloeophyllum trabeum (Pers.:Fr.) Murrill. The Chinese white poplar and Chinese fir specimens were obtained from Shandong and Hunan provinces, respectively. They were steam-heat-treated at 170, 185, 200, 215, or 230 oC with time duration of 1, 2, 3, 4, and 5 hrs in an air-tight chamber that comprised less than 2 per cent oxygen. According to the standard GB/T 13942.1-92, the decay resistance experiments were completed with the wood-rotting fungi G. trabeum on an agar block test with 12-week incubation. The results of steam-heat treatment indicated that, compared to a weight loss of 56% for untreated samples, a weight loss of 45% decreased to just 2% for Chinese white poplar with an increase in temperature from 170 to 230℃. No weight loss was observed in the steam-heat-treated China-fir heartwood, sapwood, and untreated sapwood specimens, while only a weight loss of 4.739% in untreated China-fir heartwood specimens was found.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.283

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 head0.067
GPT teacher head0.233
Teacher spread0.166 · 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

Citations18
Published2011
Admission routes1
Has abstractyes

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