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Record W2320027285 · doi:10.1515/htmp-2012-0042

Comparison of the Electronic Conduction Mechanism in MnO <sub>x</sub> -CaO-SiO <sub>2</sub> and FeO <sub>x</sub> -CaO-SiO <sub>2</sub> Slag Systems

2012· article· en· W2320027285 on OpenAlexaff
Michael Pomeroy, G G Brown, Mansoor Barati, Kenneth S. Coley

Bibliographic record

VenueHigh Temperature Materials and Processes · 2012
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsUniversity of TorontoMcMaster University
Fundersnot available
KeywordsSlag (welding)Materials scienceIonic bondingMetallurgyThermal conductionMineralogyComposite materialIonChemistry

Abstract

fetched live from OpenAlex

Abstract The electrical and electronic and ionic transference numbers were measured for slags in the system MnO-CaO-SiO 2 using the stepped potential chronoamperometry method. Transference numbers were measured over a range of oxygen partial pressure to evaluate the effect of MnO-CaO-SiO 2 . The data were compared with previously measured data for the FeO-CaO-SiO 2 system. Data were found to fit well, the Diffusion Assisted Hopping Model for electronic conduction previously develop in the authors' laboratory. The only adjustable parameter employed in fitting the data to this model, was, r * , the maximum spacing at which hopping can occur. A single value for this parameter was used for all manganese data. The value of r * obtained for the MnO-CaO-SiO 2 system was slightly smaller than that for the FeO-CaO-SiO 2 system which is in keeping with the relative magnitude of the third ionization energies for Fe and Mn.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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
Published2012
Admission routes1
Has abstractyes

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