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Record W1577845197 · doi:10.1002/9780470314821.ch22

Formation of an Alumina-Mullite Composite via Reaction Sintering

2008· book-chapter· en· W1577845197 on OpenAlexaff
Dana Goski, W. F. Caley

Bibliographic record

VenueCeramic engineering and science proceedings · 2008
Typebook-chapter
Languageen
FieldMaterials Science
TopicAdvanced ceramic materials synthesis
Canadian institutionsTechnical University of Nova Scotia
Fundersnot available
KeywordsMulliteKyaniteComposite numberMaterials scienceSinteringRheologyDispersion (optics)Composite materialAluminium silicateMineralogyCeramicChemistryQuartz

Abstract

fetched live from OpenAlex

Naturally occurring kyanite (Al2O3 SiO2) thermally decomposes above 1400C to form mullite (3Al2O3 2SiO2) and free silica. By sintering in an alumina matrix, the silica may subsequently react to form additional mullite, thereby forming an inexpensive mullite-alumina composite. Techniques including pH aging, sedimentation, micro-electrophoresis and rheology were employed to optimize aqueous processing conditions. The most stable dispersion pH for kyanite/alumina suspensions containing up to 20 vol% kyanite was established to be 3.5. Composite green bodies were cast and sintered specimens examined mineralogically using electron probe microanalysis.

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 score0.007

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)0.0020.001

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 head0.010
GPT teacher head0.210
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

Citations5
Published2008
Admission routes1
Has abstractyes

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