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Record W2470140436

Effect of process parameters on fungal resistance of MDF panels

2006· article· en· W2470140436 on OpenAlex
James Deng, Dian-Qing Yang, Xinglian Geng

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueForest Products Journal · 2006
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsMoldMaterials scienceFactorial experimentComposite materialRefining (metallurgy)Water contentFiberboardPulp and paper industryMetallurgyMathematicsEngineering
DOInot available

Abstract

fetched live from OpenAlex

A study was conducted at Forintek Canada Corporation to investigate the effects of different refining process conditions and resin contents on mold growth rates. A refining experiment was carried out with a fractional factorial design. Preheating retention time, steam pressure, resin content, and panel density were chosen as the factors, each at two different levels. Twenty-four laboratory panels were made with eight different manufacturing processes. Mold growth on the medium density fiberboard (MDF) panels was quantified according to a modified ASTM standard (D 3273-94). Experimental results showed that preheating temperature and moisture content at the completion of the mold growth test positively correlated to the mold growth rate. Mold growth rate was lower with higher panel modulus of rupture (MOR) tested after a 1-hour boiling treatment and higher initial moisture. To a lesser extent, mold growth was reduced with increased resin content and dry panel MOR.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.380

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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