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Record W158939641

Changes in Physical Properties of Yellow Birch Below and Above the Fiber Saturation Point

2006· article· en· W158939641 on OpenAlexfundno aff
Giana Almeida, Roger E. Hernández

Bibliographic record

VenueWood and Fiber Science (Society of Wood Science and Technology) · 2006
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsRelative humidityEquilibrium moisture contentSorptionSaturation (graph theory)ShrinkageWater contentComposite materialMoistureBound waterMaterials scienceHysteresisHumidityVapor pressureFree waterChemistryMineralogyThermodynamicsGeotechnical engineeringGeologyAdsorptionMathematics
DOInot available

Abstract

fetched live from OpenAlex

Two experimental techniques were used to perform moisture sorption tests at 25°C on specimens of yellow birch sapwood. The first used saturated salt solutions (from 33% to 90% relative humidity), and the second used the pressure membrane method (above 96% relative humidity). These sorption tests were combined with dimensional measurements and perpendicular-to-the-grain tangential compression tests. Results showed that at equilibrium moisture content, radial, tangential, and volumetric shrinkage, as well as changes in transverse strength, occur above the fiber saturation point. This behavior can be explained by the effect of hysteresis at saturation on wood properties. This hysteresis indicates that loss of bound water takes place in the presence of liquid water, which contradicts the concept of FSP. The initial equilibrium moisture content at which bound water is removed from yellow birch was about 41%.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.191
Teacher spread0.182 · 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 source (direct Gemma or distilled Codex), 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

Citations36
Published2006
Admission routes1
Has abstractyes

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