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Record W2771292630 · doi:10.1002/slct.201701551

The Influence of Cold Caustic Extraction on the Purity, Accessibility and Reactivity of Dissolving‐Grade Pulp

2017· article· en· W2771292630 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

VenueChemistrySelect · 2017
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of British Columbia
FundersChina Scholarship CouncilMinistry of Education of the People's Republic of China
KeywordsDissolving pulpCellulosePulp (tooth)DissolutionChemistryPulp and paper industryHydrolysisKraft processCellulaseSulfuric acidChemical engineeringKraft paperOrganic chemistryDentistry

Abstract

fetched live from OpenAlex

Abstract Prehydrolysis and cold caustic extraction (CCE) are two effective approaches to convert the traditional Kraft pulp to a dissolving‐grade pulp. Compared to prehydrolysis, CCE has several positive attributes but reduces final pulp reactivity. To gain insight into the factors that influence the reactivity of CCE treated cellulose, we compared the surface morphology, supramolecular properties and fibre properties of commercial dissolving pulp from prehydrolysis to dissolving grade cellulose upgraded using CCE. CCE treatment promoted the fibril aggregation and modified the initial cellulose I on Kraft pulps to cellulose II, thus decreasing final pulp reactivity. Various “post‐treatments” such as mechanical refining, steam explosion, induction of fibre kink and curl, sulfuric acid hydrolysis and endoglucanase hydrolysis effectively recover the reactivity lost during the production of dissolving pulp cellulose using a CCE step. Mechanical refining combined with endoglucanase treatment had the greatest effect increasing the reactivity from 32% to 75%.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.084
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.033
GPT teacher head0.350
Teacher spread0.317 · 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