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Surface characterisation techniques in the study and conservation of art and archaeological artefacts: a review

2010· review· en· W1973060962 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials Technology · 2010
Typereview
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsRoyal Ontario Museum
Fundersnot available
KeywordsConservationArchaeologyCover (algebra)Field (mathematics)HistoryEngineeringGeographyEnvironmental planningMechanical engineering

Abstract

fetched live from OpenAlex

Key issues related to surfaces and materials in the study and conservation of archaeological, artistic and historical objects are presented and illustrated with case studies. The materials cover a relatively broad chronological and compositional range. An important objective of the review is to inform the materials science and engineering community of the problems and needs of conservators, archaeologists, conservation specialists, art historians, archaeometrists and researchers in the field of ancient materials. In this way, improved technical information on methods designed to identify surface treatments and surface finishes, development of a common language among humanities and scientific researchers, and awareness of new applications appropriate in archaeometric studies can be promoted.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.073
GPT teacher head0.313
Teacher spread0.241 · 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