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Record W1965417360 · doi:10.5558/tfc85401-3

Canadian pulp fibre morphology: Superiority and considerations for end use potential

2009· article· en· W1965417360 on OpenAlexaffvenueabout
Paul Watson, Michael D. Bradley

Bibliographic record

VenueThe Forestry Chronicle · 2009
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsCanfor Pulp Products (Canada)
Fundersnot available
KeywordsPulp (tooth)SoftwoodUltimate tensile strengthKraft paperPulp and paper industryKraft processReinforcementComposite materialMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Four physical attributes of fibres confer the end use potential of a pulp, namely fibre length, fibre coarseness, fibre strength and uniformity. Long, slender, fine fibred pulps, which are low in thick-walled summerwood content, provide superior reinforcement strength. The natural species endowment that Canada enjoys can, when accompanied by superior operational performance and technical vision, result in significant advantages for strategically focused companies and their customers. Factor and multivariate analysis of more than 60 industrial pulp samples confirm that on the basis of fundamental morphological differences, Canadian pulps exhibit clear superiority. Canadian northern bleached softwood kraft pulp is the undoubted industry leader, yet unrealized potential still exists, and additional research effort is required, to maintain this market position. Key words: kraft pulp, softwood, fibre morphology, intrinsic properties, length, coarseness, fibre strength, tensile strength, biogeoclimatic zone, factor analysis, reinforcement, premium reinforcement pulp, PRP, refining

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.901

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.211
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations22
Published2009
Admission routes3
Has abstractyes

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