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Record W1986641003 · doi:10.1002/cjce.5450780134

Mixing of a lignin‐based slurry fuel

2000· article· en· W1986641003 on OpenAlexafffundvenue
Duško Pošarac, A. P. Watkinson

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsUniversity of British Columbia
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryKraft processKraft paperForestryPulp and paper industryEngineering

Abstract

fetched live from OpenAlex

Abstract Lignin‐based slurry fuels are a potential alternative to fossil fuels in kraft pulp mills. Lignogels — mixtures of lignin, fuel oil, water and surfactant — are non‐Newtonian fluids, with shear‐thinning and thixotropic behaviour. Their mixing was investigated in tanks with volumes of 3 and 30 L. An A310 hydrofoil impeller was used in all experiments. Results were compared with measurements in Newtonian fluids, used to characterize the impeller over a broad range of Reynolds numbers (1–500 000). An aqueous CMC solution was also used for characterization of the impeller and estimation of the Metzner‐Otto constant. Results in the transition region were corrected by introduction of two empirical parameters.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.407

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 head0.004
GPT teacher head0.155
Teacher spread0.151 · 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 designSimulation or modeling
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

Citations4
Published2000
Admission routes3
Has abstractyes

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