MétaCan
Menu
Back to cohort
Record W2808901927 · doi:10.1038/s41598-018-27714-5

Recovery of Degraded-Beyond-Recognition 19th Century Daguerreotypes with Rapid High Dynamic Range Elemental X-ray Fluorescence Imaging of Mercury L Emission

2018· article· en· W2808901927 on OpenAlexafffund
Madalena S. Kozachuk, Tsun‐Kong Sham, Ronald R. Martin, Andrew J. Nelson, I. Coulthard, John McElhone

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsNational Museum of Fine Arts of QuebecCanadian Light Source (Canada)Western University
FundersNational Institute of General Medical SciencesNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchDivision of Materials ResearchCanada Research ChairsNational Science FoundationNational Institutes of HealthUniversity of SaskatchewanCanadian Light Source
KeywordsMercury (programming language)Materials scienceSynchrotronSpecular reflectionCopperOpticsComputer scienceMetallurgyPhysics

Abstract

fetched live from OpenAlex

Abstract A daguerreotype image, the first commercialized photographic process, is composed of silver-mercury, and often silver-mercury-gold amalgam particles on the surface of a silver-coated copper plate. Specular and diffuse reflectance of light from these image particles produces the range of gray tones that typify these 19 th century images. By mapping the mercury distribution with rapid-scanning, synchrotron-based micro-X-ray fluorescence (μ-XRF) imaging, full portraits, which to the naked eye are obscured entirely by extensive corrosion, can be retrieved in a non-invasive, non-contact, and non-destructive manner. This work furthers the chemical understanding regarding the production of these images and suggests that mercury is retained in the image particles despite surface degradation. Most importantly, μ-XRF imaging provides curators with an image recovery method for degraded daguerreotypes, even if the artifact’s condition is beyond traditional conservation treatments.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.996

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.217
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.

Study designBench or experimental
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

Citations19
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueScientific ReportsSame topicCultural Heritage Materials AnalysisFrench-language works237,207