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Record W2509089794 · doi:10.1002/srin.200001332

Oxidation-reduction equilibria of ferrous/ferric ions in oxide melts

2000· article· en· W2509089794 on OpenAlexaff
Seiji Ohashi, Masumi Kashimura, Yuichi Uchida, Alexander McLean, Masanori Iwase

Bibliographic record

VenueSteel Research · 2000
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFerrousFerricFerric ionOxideIonReduction (mathematics)ChemistryFERRIC IRONInorganic chemistryOxidation reductionRedoxMetallurgyMaterials scienceOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

Oxidation-reduction equilibrium experiments were conducted with oxide melts containing CaO, Li2O, Al2O3, ZnO, B2O3, SiO2 and small concentrations of iron oxide. The results indicated that for compositions within the acidic regime, the ratio {(Fe3+)/(Fe2+) PO21/4} decreased with an increase in basicity while for relatively basic melts, the ratio increased with an increase in basicity. This variation of {(Fe3+)/(Fe2+) PO21/4} could be interpreted in terms of the optical basicity of the glass melts and is consistent with the following expressions for the red-ox equilibria within acidic and relatively basic melts, respectively: In an acidic melt, the temperature dependence of the reaction yielded an enthalpy value which was in excellent agreement with the enthalpy change for the reaction: For a relatively basic melt, the enthalpy value for the corresponding reaction was about half of that found for the acidic melt.

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 score0.002
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 head0.051
GPT teacher head0.331
Teacher spread0.280 · 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

Citations1
Published2000
Admission routes1
Has abstractyes

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