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Record W2801062906 · doi:10.3138/ngcr.9-003

Applying Nanoscience to Daguerreotypes: Understanding and Preserving the First Form of the Photograph / Appliquer la nanoscience aux daguerréotypes : comprendre et préserver la première forme de photographie

2018· article· fr· W2801062906 on OpenAlexvenueaboutno aff
Madalena S. Kozachuk, John McElhone

Bibliographic record

VenueNational Gallery of Canada Review · 2018
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
FundersDivision of Materials ResearchNational Institute of General Medical SciencesNational Institutes of HealthNational Science Foundation
KeywordsSynchrotronPhotographyFluorescenceArt historyNanotechnologyArtPhysicsOpticsMaterials scienceVisual arts

Abstract

fetched live from OpenAlex

This research describes a preliminary study conducted as part of a collaboration between Western University (London, Ontario) and the Canadian Photography Institute of the National Gallery of Canada (NGC). Daguerreotypes with varying degrees of deterioration were supplied by the NGC conservation department's study collection. Synchrotron- and laboratory-based techniques were used to examine the plates before they were electrocleaned. Synchrotron-based X-ray absorption spectroscopy and X-ray fluorescence microscopy, conducted at the Canadian Light Source (Saskatoon, Saskatchewan), enabled a chemical characterization of the surface alongside fluorescence mapping. Rapid-scanning fluorescence imaging recorded at the Cornell High Energy Synchrotron Source (Ithaca, New York) showed that the fluorescence signal from mercury could be used to retrieve images obscured by chemical and physical deterioration. The improved electrocleaning set-up established at the NGC and the implications of the subsequent studies are discussed.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.892
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.042
GPT teacher head0.276
Teacher spread0.234 · 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 designNot applicable
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

Citations3
Published2018
Admission routes2
Has abstractyes

Explore more

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