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Record W2731837552

Development of a Free Lime Monitoring System for the Kraft Recovery Process using Zeta Potential

2014· dissertation· en· W2731837552 on OpenAlexaff
Ren Wei

Bibliographic record

VenueTSpace (University of Toronto) · 2014
Typedissertation
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLimeKraft paperZeta potentialProcess (computing)Process engineeringEngineeringPulp and paper industryEnvironmental scienceWaste managementComputer scienceMaterials scienceChemical engineeringMetallurgyOperating system
DOInot available

Abstract

fetched live from OpenAlex

The presence of Ca(OH)2 (or free lime) in lime mud can cause many problems in the recovery process of kraft pulp mills. Conventional free lime analyses require extensive laboratory work and give inconsistent results. A systematic study was performed to determine if zeta potential, a quickly measurable dispersion characteristic, can be used to indicate the presence of free lime in the recovery process. Measurements were made on synthetic wet lime mud to simulate samples collected after the white liquor clarifier in pulp mills. The results show that zeta potential increases from negative to positive when the free lime content in the lime mud exceeds a critical threshold. This change from negative to positive zeta potential of the lime mud slurry can be used as a basis for developing an on-line monitoring system that effectively detects free lime in the lime mud in order to avoid problems associated with overliming in the recovery process.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.243
Teacher spread0.225 · 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 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
Published2014
Admission routes1
Has abstractyes

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