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Record W2054956413 · doi:10.1179/cmq.2002.41.4.451

Oxygen Softening of Lead: On-Line Measurement of Bullion Quality

2002· article· en· W2054956413 on OpenAlexfundno aff
Joël P. T. Kapusta, T. R. Meadowcroft, Greg Richards

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2002
Typearticle
Languageen
FieldEngineering
TopicElectrical and Bioimpedance Tomography
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBullionAntimonyArsenicMetallurgyOxygenLead (geology)ChemistryMaterials scienceGeology

Abstract

fetched live from OpenAlex

Oxygen softening of lead bullion is used at Teck Cominco's Trail smelter to reduce the level of arsenic and antimony in crude bullion to make a product suitable for anode refining. Since impurity content and oxygen potential of the bullion are thermodynamically related, on-line determination of the arsenic and antimony levels without the need for sampling hot metal can be achieved by monitoring the oxygen potential of the lead bullion. An oxygen probe for continuous measurements in molten lead has been designed in the laboratory. The probe can be schematically represented asstainless steel, [O]in lead bullion|ZrO2 – Y2O3|Cu – Cu2O, stainless steelOnce it was established that the probe was giving satisfactory measurements in the laboratory, quick response to temperature and oxygen potential changes, a testing campaign was carried out in an industrial environment. The campaign was successful and a correlation between measured electromotive force (EMF) and bullion content in arsenic and antimony was established as follows(we%)As+Sb = −1.366+10.26×10−3 (mV)Measured where (wt%)As+Sb is the combined (As+Sb) bullion content in wt% and (mV)Measured is the measured EMF in mV.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score0.598

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 head0.048
GPT teacher head0.226
Teacher spread0.177 · 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 designOther design
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

Citations2
Published2002
Admission routes1
Has abstractyes

Explore more

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