MétaCan
Menu
Back to cohort
Record W4409760022 · doi:10.1080/00393630.2025.2469475

Risk-based Decision-making Informed by Analysis of an Early Nineteenth-century Manuscript Containing Smalt

2025· article· en· W4409760022 on OpenAlex
Tiffany Eng Moore, Maeve M. Moriarty, Stephanie Barnes, Crystal Maitland, K.J. Bladek, Christine McNair

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueStudies in Conservation · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArtHistory

Abstract

fetched live from OpenAlex

This paper reviews a collaborative examination and analysis of an early nineteenth-century music manuscript at the Canadian Conservation Institute. Collaboration between conservation scientists and conservators helped process scientific information, hazards, and treatment decisions to complete the arc of planning, treatment execution, and future care recommendations for the client. An unexpected result during the initial analysis of the pigments flagged the presence of arsenic on the painted and unpainted areas of the textblock. Initial hypotheses were that it could have derived from an application of pesticide on the binding or that it was part of the papermaking process. To characterize the nature of the arsenic more fully and to attempt to understand the level of risk during handling, further analysis was carried out. Through the analysis, it was determined that the source of arsenic in the manuscript is smalt – a blue glassy colourant, added to the paper during manufacture to make it appear whiter; there was no indication of an arsenical pesticide found. This case study provoked interesting discussions regarding the contextualizing of risk and analysis results when working with an unexpected finding of potential hazards, both during the execution of a conservation treatment, and in recommending care during handling and storage.

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)0.002
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 score0.030
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.303
Teacher spread0.254 · 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