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Record W3039765730 · doi:10.1186/s10086-020-01892-1

High-pressure densification and hydrophobic coating for enhancing the mechanical properties and dimensional stability of soft poplar wood boards

2020· article· en· W3039765730 on OpenAlex

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

VenueJournal of Wood Science · 2020
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsMcGill University
FundersZhejiang University
KeywordsMaterials scienceComposite materialSwellingCoatingRelative humidityEpoxy

Abstract

fetched live from OpenAlex

Abstract Effects of high-pressure (HP) treatment on densification of poplar sapwood boards and subsequent coatings were evaluated. Tung oil (TO) and epoxy resin (ER)-coated treatments were used to improve the dimensional stability of HP-densified wood. The density of the wood after HP densification increased from 450 ± 50 kg/m 3 for the control to 960 ± 20 kg/m 3 at 125 MPa. This process also resulted in the average thickness of HP-densified boards to reduce significantly from 29.7 ± 0.11 mm for the control to 18.8 ± 0.53 mm after HP densification at 25 MPa and 14.3 ± 0.10 mm after 125 MPa treatment for 30 s. The mechanical strength measured as the hardness of densified wood significantly increased from 35% at 25 MPa to 96% at 125 MPa treatment, compared to untreated wood. As expected both TO and ER-coated treatments significantly reduced set-recovery of densified wood when stored at four relative humidity environments. ER showed better anti-swelling performance than TO, and would be a better choice.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.193

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 head0.032
GPT teacher head0.213
Teacher spread0.181 · 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