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Understanding the limits of screening operation. Part 2: Characterizing the operational window

2024· article· en· W4393256196 on OpenAlexafffund
Miguel E. Villalba, James A. Olson, D. Mark Martinez

Bibliographic record

VenueBioResources · 2024
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWindow (computing)Materials scienceTherapeutic windowReliability engineeringProcess engineeringComputer scienceEngineeringMedicineOperating system

Abstract

fetched live from OpenAlex

The limits of the pulp screening operation can be defined as the maximum throughput before the apertures start to plug permanently. This two-part article sought insights into the limits of screening operation. In part two, the operational window of the screen was characterized by performing a series of screening trials with different pulp furnishes, where the plugging point was conventionally measured with the pressure signal. The limits of operation, given by a slot velocity and rotor speed contour, showed a robust linear relationship at the point of plugging, which depended on the ratio of the fibre length to aperture size. For size ratios less than 1.5, the screen did not plug under the conditions tested. In addition, the plugging detection tool was conceptualized in part one based on the kurtosis of the distribution of fluctuation peaks, and it was employed here. Effectively, deviations from the Gaussian distribution of the pressure fluctuation peaks signal the onset of screen plugging. Thus, the utility of this tool was confirmed for detecting plugs using readily available pressure fluctuation data in pilot-scale screening operations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.249
GPT teacher head0.374
Teacher spread0.125 · 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 designNot applicable
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

Citations1
Published2024
Admission routes2
Has abstractyes

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