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Record W1490406556 · doi:10.15376/biores.6.4.5099-5109

Use of a dynamic sheet former (DSF) to examine the effect of filler addition and white water recirculation on fine papers containing high-yield pulp

2011· article· en· W1490406556 on OpenAlex

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

VenueBioResources · 2011
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsFPInnovationsUniversity of New Brunswick
Fundersnot available
KeywordsFiller (materials)Pulp (tooth)Materials scienceYield (engineering)Composite materialPulp and paper industryEngineeringDentistry

Abstract

fetched live from OpenAlex

With increased interest in using high-yield pulps (HYP) in uncoated and coated wood-free paper, Such tests were carried out by means of a Dynamic Sheet Former (DSF) sheet with white water recirculation, considering the high fines content of HYP and the usually high filler content in fine papers. In this study, we evaluated the use of a DSF that is equipped with a white water recirculation tank for making oriented sheets under various conditions. The effects of different factors such as operational variables, use of retention aids, and recirculation of white water were examined and clarified in terms of retention of fines and fillers as well as their impact on paper properties. The effect of HYP content on filler retention was also examined.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.130
Threshold uncertainty score0.358

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 head0.022
GPT teacher head0.184
Teacher spread0.162 · 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