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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 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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.030
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 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

Citations3
Published2014
Admission routes1
Has abstractyes

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