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Record W2040698192 · doi:10.1002/sia.2454

The middle lamella remainders on the surface of various mechanical pulp fibres

2006· article· en· W2040698192 on OpenAlexaff
Kecheng Li, Xuequan Tan, Dongbo Yan

Bibliographic record

VenueSurface and Interface Analysis · 2006
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMiddle lamellaPulp (tooth)Scanning electron microscopeX-ray photoelectron spectroscopyLigninLamella (surface anatomy)Materials scienceComposite materialChemistryChemical engineeringOrganic chemistryDentistry

Abstract

fetched live from OpenAlex

Abstract The surfaces of various mechanical pulp fibres, including thermomechanical pulp (TMP), chemithermomechanical pulp (CTMP), and alkaline peroxide mechanical pulp (APMP) fibres, were characterized using scanning electron microscopy (SEM), atomic force microscopy (AFM), and X‐ray photoelectron spectroscopy (XPS). With SEM and AFM, the middle lamella material was observed to be non‐fibrillar and patch‐like, while the fibre secondary wall was observed to have a micro‐fibrillar structure. It was found that after the first‐stage refiner, lignin‐rich middle lamella remainders were present on the fibre surface of all three pulps, although most of the fibre surfaces exhibited a micro‐fibrillar structure. After the final‐stage refining, large amounts of granules were present on the TMP fibre surface. In contrast, most middle lamella remainders were still visible on the surface of CTMP fibres after the final‐stage refining and even after peroxide bleaching. XPS results have confirmed that the non‐fibrillar surface material is the lignin‐rich middle lamella remainder that contribute to the high surface lignin concentration. Copyright © 2006 John Wiley & Sons, Ltd.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.026
GPT teacher head0.279
Teacher spread0.253 · 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

Citations26
Published2006
Admission routes1
Has abstractyes

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