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Comparing Properties of North American Manufactured Particleboard and Medium Density Fiberboard - Part II: Medium Density Fiberboard

2015· article· en· W1961735584 on OpenAlexaff
Jörn Dettmer, Gregory D. Smith

Bibliographic record

VenueBioResources · 2015
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedium density fiberboardFiberboardMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The properties of medium density fiberboard (MDF) derived from different manufacturing plants were compared. Each plant provided 5 full-sized (2440 by 1220 mm) 155-grade panels that were tested according to ANSI A208.2-2009. None of the panels met the recommended value for Internal Bond (IB). Mean values for Thickness Swell (TS) were all significantly different, with one manufacturer below the standard. Three manufacturers exceeded the recommended face Screw Withdrawal Resistance (fSWR) values, one was equal to it, and one failed. Three manufacturers exceeded the edge SWR (eSWR) standard, and the remaining two fell below. Two manufacturers met the standard for Modulus of Rupture (MOR), and only one manufacturer failed to meet the Modulus of Elasticity (MOE) requirements. Linear Expansion (LE) was evaluated for a RH change from 50 to 90%. The panels made with pMDI-resin consistently had some of the highest mean values for MOR, MOE, fSWR, and IB and exhibited good performance in the TS test.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.197
Teacher spread0.165 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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