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Record W2768967305 · doi:10.1111/jace.15346

The production of a lead glaze with galena: Thermal transformations in the PbS–SiO <sub>2</sub> system

2017· article· en· W2768967305 on OpenAlexfundno aff
Roberta Di Febo, Judit Molera, Trinitat Pradell, Joan Carles Melgarejo i Draper, Josep Madrenas, Oriol Vallcorba

Bibliographic record

VenueJournal of the American Ceramic Society · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
FundersMinisterio de Ciencia e InnovaciónGeneralitat de CatalunyaUniversity of Victoria
KeywordsGalenaGlazeMineralogyPhase diagramPhase (matter)Materials scienceAnalytical Chemistry (journal)CrystallographyInorganic chemistryMetallurgyChemistryCeramicOrganic chemistrySphalerite

Abstract

fetched live from OpenAlex

Abstract Galena, also known as PbS, was widely used in the production of lead glazes from the beginning of the 18th century to the second half of the 20th century. Although the PbO‐SiO 2 system has been studied for years, the PbS–SiO 2 phase diagram, involved in the formation of a glaze with galena, has not yet been investigated. Temperature transformations for the system 75 wt% PbS‐25 wt% SiO 2 are investigated in a high‐temperature resolved X‐ray diffraction experiment with synchrotron radiation and compared to those of the equivalent system 70 wt% PbO‐30 wt% SiO 2 . Lanarkite, PbO·PbSO 4 , is the phase predominantly formed as soon as galena decomposes during the heating. The results show that the system melts at a temperature higher than the PbO–SiO 2 system, but far lower than those expected for the PbO–PbSO 4 –PbS system. A historical misfired lead glaze produced with galena is also studied. The presence of galena, lanarkite, and mattheddleite, Pb 10 (SiO 4 ) 3.5 (SO 4 ) 2 Cl 2, is determined and discussed in terms of the composition of the galena mineral used and the firing conditions in light of the high‐temperature transformations previously obtained.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.936

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.018
GPT teacher head0.220
Teacher spread0.203 · 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 designQualitative
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

Citations10
Published2017
Admission routes1
Has abstractyes

Explore more

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