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The influence of consistency and fibre length on the yield stress of OCC pulp fibre suspensions

2017· article· en· W2758323978 on OpenAlexaff
Hui Cai, Zhaoyang Yuan, Xin Zhang, Hui Zhang, James A. Olson

Bibliographic record

VenueBioResources · 2017
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsState Key Laboratory of Pulp and Paper Engineering
KeywordsPulp (tooth)Materials scienceSlurryComposite materialConsistency (knowledge bases)Pulp and paper industryMathematicsEngineeringDentistry

Abstract

fetched live from OpenAlex

The effect of fibre length on the yield stress of recycled old corrugated containers (OCC) pulp fibre suspensions was investigated. Two types of OCC pulps were divided into four fractions based on the fibre length with a Bauer-McNett classifier. The yield stress of each fraction was measured using the shear stress ramp method at pulp consistency ranging from 0.5% to 2.5% (w/v). The results showed that both pulp consistency and fibre length had significant effects on the yield stress of OCC pulp suspensions, and the yield stress was greater with increasing fibre length and pulp consistency. Moreover, the effect of consistency in OCC pulp suspension with long fibres on the yield stress was stronger than in the slurry with short fibres.

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 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)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.036
GPT teacher head0.289
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 teacher head, 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

Citations9
Published2017
Admission routes1
Has abstractyes

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