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Record W1997609269 · doi:10.1515/hf.2007.022

Characterization of thin water layers in pulp by tritium exchange. Part 2: Effect of refining on water absorption

2007· article· en· W1997609269 on OpenAlexaboutno aff
Frances L. Walsh, Sujit Banerjee

Bibliographic record

VenueHolzforschung · 2007
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsnot available
Fundersnot available
KeywordsKraft processPulp (tooth)Absorption of waterChemistryMonolayerBlack liquorMaterials scienceRefining (metallurgy)Kraft paperComposite materialLigninMetallurgyNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The surface area of pulp increases upon refining, which also increases the quantity of bound water. The subfraction of water attached to the surface as a monolayer can be determined by adding tritiated water to a pulp/water suspension and measuring the distribution of tritium between the pulp and bulk water. For bleached kraft pulp the tightly bound water slowly increases with progressive refining, increases sharply at 360 ml Canadian Standard Freeness (CSF), and then falls below CSF 220 ml. The fiber saturation point displays a similar profile, although the changes are much less pronounced. It is proposed that refining occurs in three discrete stages. First, refining down to CSF 360 ml removes the primary cell wall and S1 layer, while the S2 layer begins to swell. Next, internal delamination occurs within the S2 layer between CSF 360 and 220 ml, as confirmed by scanning electron microscopy. The onset of delamination is sudden: dramatic changes in fiber structure occur at CSF 360 ml, at which point the tightly bound water content rapidly increases. Finally, fiber destruction occurs below CSF 220 ml.

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)0.001
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 score0.002
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.205
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

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

Citations5
Published2007
Admission routes1
Has abstractyes

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