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Record W4406080356 · doi:10.1016/j.ara.2024.100587

Two firings of the bronze vessel casting moulds: Distinction between firing and casting of the Late Shang and Western Zhou silt moulds

2025· article· en· W4406080356 on OpenAlexaffabout
Wen Yin Cheng

Bibliographic record

VenueArchaeological Research in Asia · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsCastingBronzeArchaeologySiltWestern ZhouShang dynastyGeologyAncient historyGeographyMetallurgyHistoryMaterials scienceChinaPaleontology

Abstract

fetched live from OpenAlex

This study aims to differentiate between the firing and casting processes of the Late Shang and Western Zhou bronze vessel casting moulds. While previous research has primarily focused on the moulds' firing temperature and heat resistance, this study delves deeper into the distinct stages of firing and casting. By analyzing the three mould types housed at the Royal Ontario Museum (ROM) using petrography and scanning electron microscope (SEM), this research introduces a new method to distinguish between moulds that were later used and those discarded owing to some imperfections. The study also highlights the variations in firing atmosphere and technological preferences of the artisans, shedding light on the complex processes involved in bronze casting mould production. The findings provide valuable insights into the organization of bronze casting and the technological advancements of the Late Shang and Western Zhou dynasties. • Identifying firing and casting methods • Petrographic and scanning electron microscope analysis on heat alteration. • Chinese bronze casting technology • Reaction of heat to silt rich material

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.137
GPT teacher head0.361
Teacher spread0.223 · 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 designObservational
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
Published2025
Admission routes2
Has abstractyes

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