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Record W2913900906 · doi:10.1515/npprj-2018-0039

Power–gap relationships in low consistency refining

2019· article· en· W2913900906 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNordic Pulp & Paper Research Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaFPInnovationsBC Hydro
KeywordsRefining (metallurgy)Consistency (knowledge bases)Power (physics)Industrial chemistryProcess engineeringMaterials scienceComputer scienceEngineeringBiochemical engineeringArtificial intelligenceMetallurgyThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Distance between stationary and rotating refining plates, gap, has a direct and significant impact on refining power. Gap is almost universally used to control power in low consistency refining operations. The relationship between power and gap are affected by refiner size, pulp type, plate pattern and refining conditions. In this study, a correlation was developed to describe the power-gap relationships at a wide range of refining conditions and furnish. The correlation was developed using pilot-scale refining data of mechanical pulps. Results showed that a properly defined dimensionless power number is suitable to describe refining power as well as to compare different refiners under the same grounds. The developed correlation was also used to predict mill-scale refining data showing good agreement with between predicted and measured values. Finally, experimental data from force sensor measurements supports the correlation's theoretical assumptions.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.304
Teacher spread0.253 · 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