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Record W2350422273

Comparative Pulping Properties of Eucalyptus urograndis × E.grandis and Acacia mangium Willd.Woods Using P-RC APMP Process

2008· article· en· W2350422273 on OpenAlexaboutno aff
Guigan Fang

Bibliographic record

VenueLinchan huaxue yu gongye · 2008
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsAcacia mangiumPulp (tooth)Pulp and paper industryEucalyptusUltimate tensile strengthChemistryHardwoodBotanyComposite materialMaterials science
DOInot available

Abstract

fetched live from OpenAlex

Pulping properties of Eucalyptus urograndis×E.grandis(E.u.×E.g.) and Acacia mangium Willd.wood chips were investigated by using preconditioning refinerchemical alkaline peroxide mechanical pulping(P-RC APMP) process.Specific refining energies were recorded and both physical properties and optical properties of pulps were evaluated.Results show that similar brightness of P-RC APMP pulps could be produced from both E.u.× E.g.and A.mangium wood chips.At the chemical dosage level of H2O2 4.0 % and NaOH 3.5 %,which is a very low chemical consumption,pulp brightness of both pulps was able to reach 75 % ISO.The pulp yield of A.mangium wood chips was 3.0 % higher than that of E.u.× E.g.wood chip.At the freeness level of 250 mL Canadian Standard Freeness(CSF),pulps from A.mangium wood chips was much stronger than that from E.u.× E.g..For example,the tensile strength of P-RC APMP pulp from A.mangium was above 26 N·m/g,about 30 % higher than that of E.u.× E.g.pulp;Further refining could improve chemimechanical pulp strength.For the same CSF level,pulping of A.mangium wood chips requires more refining energy than that of E.u.× E.g.wood chips.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.046
GPT teacher head0.240
Teacher spread0.195 · 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.

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

Citations0
Published2008
Admission routes1
Has abstractyes

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