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Record W4241256509 · doi:10.1002/9781118888438.ch139

Developing a New Process Indicator Based on the Relationship Between an Electrolysis Cell Impurity Balance and Its Incidents

2014· other· en· W4241256509 on OpenAlexaff
Lukas Dion, László I. Kiss, Dany Lavoie, Jean‐Paul Arvisais

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicMetal Extraction and Bioleaching
Canadian institutionsAluminerie Alouette (Canada)Université du Québec à Chicoutimi
Fundersnot available
KeywordsImpurityElectrolysisVanadiumPartition (number theory)AnodeProcess (computing)Balance (ability)Computer scienceChemistryAnalytical Chemistry (journal)Inorganic chemistryEnvironmental chemistryMathematicsPsychologyPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

This chapter contains sections titled: Introduction Initial Case Impurity Partition Factors Correlation between Anodic Incidents and the Vanadium Content in the Aluminum Indicator Developed by Alouette to Identify Cells with Anodic Incidents Conclusion

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.739
Threshold uncertainty score0.588

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 head0.030
GPT teacher head0.273
Teacher spread0.242 · 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 designObservational
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

Citations3
Published2014
Admission routes1
Has abstractyes

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