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Record W2090030282 · doi:10.1007/s00226-015-0728-6

A review of preparation of binderless fiberboards and its self-bonding mechanism

2015· review· en· W2090030282 on OpenAlex
Daihui Zhang, An-Jiang Zhang, Lixin Xue

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

VenueWood Science and Technology · 2015
Typereview
Languageen
FieldMaterials Science
Topicbiodegradable polymer synthesis and properties
Canadian institutionsMcGill University
Fundersnot available
KeywordsFiberboardRaw materialMaterials scienceAdhesivePressingBonding strengthProcess (computing)Waste managementProcess engineeringComposite materialEngineeringChemistryOrganic chemistryComputer science

Abstract

fetched live from OpenAlex

The demand for fiberboards has been growing in recent years. However, emission of formaldehyde, which was the main component of adhesives in fiberboards, has caused environmental and health concerns. Industries are therefore pursuing green chemistry technologies to eliminate these concerns. Binderless fiberboards appeared to be such candidates since the manufacturing process involved no resin addition. Several potential mechanisms of the formation of binderless fiberboards have been proposed. Chemical changes of components in lignocellulosic materials were expected to occur, and self-bonding achieved during hot pressing provided main bonding strength. This review summarized various aspects of binderless fiberboard production, particularly feasibility of different raw materials, chemical and enzymatic pretreatments of raw materials, manufacturing process, as well as the potential mechanism of self-bonding. Furthermore, further work that may benefit the elucidation of self-bonding mechanism was discussed.

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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.884
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.053
GPT teacher head0.327
Teacher spread0.274 · 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