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Record W7037850949

Evaporator Scaling at a Zero-effluent BCTMP Mill

2022· dissertation· W7037850949 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace · 2022
Typedissertation
Language
FieldComputer Science
TopicAdvanced Database Systems and Queries
Canadian institutionsnot available
Fundersnot available
KeywordsEffluentMillPipingPulp millBoiler feedwaterPulp (tooth)ScalingSolubilityWork (physics)
DOInot available

Abstract

fetched live from OpenAlex

Over the last few decades, many pulp mills have implemented measures to reduce water consumption and maximize effluent reuse. With increasing closure of the effluent cycle, species can accumulate in the process streams and deposit in equipment and piping which negatively impacts the mill operations and product quality. This work focuses on scale formation in the evaporators of a zero-effluent bleached chemi-thermo-mechanical pulp (BCTMP) mill in Canada. The evaporators are used to concentrate the effluent and recover water for process use. In this work, the liquor-side scale deposits were characterized, and a mass balance study was carried out to identify the sources of scaling components in the streams to the evaporators. The third part of this work involved solubility experiments to determine the effects of temperature, degree of concentration, and pH on the solubility of the scaling components. The mass balance and solubility data provide information the mill can use to develop mitigation strategies.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.888
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.344
Teacher spread0.320 · 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 designNot applicable
Domainnot available
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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