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Record W2791560694

Spectroscopic approaches for studying faint text on a wooden tally from Invincible (1758)

2018· article· en· W2791560694 on OpenAlexfundno aff
Douglas M. Goltz, Brent Piniuta, Erwin Huebner, Michael Attas, E. A. Cloutis, John Broomhead

Bibliographic record

VenueWinnSpace (University of Winnipeg) · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Materials Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLinguisticsPsychologyHistoryPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

In this study we describe the application of X-ray fluorescence, variable pressure scanning electron microscopy and visible (420-720 nm) hyperspectral imaging to assess the surface properties of a wood tally stick that was recovered from the 3rd rate Invincible. The Invincible was a wooden warship that sunk in 1758. The main objective of this work was to improve the legibility of very faint text that was detected on the surface of one of the three tally sticks used in this project. For imaging, an ultraviolet light source was used to achieve reasonable contrast between the text and the wood and the optimal wavelength was found to be 365nm. Single band images at 550 nm gave the best contrast, particularly if flat fielding was used to compensate for uneven lighting of the wooden surface. Finally, X-ray fluorescence (XRF) and SEM were used to assess the wood and possibly identify the material used to write on the tally stick. The scanning electron microscopy (SEM) images did not reveal the presence of any graphite particles or ink deposits, but the XRF indicated that there were higher levels of Fe where text was detected, which may indicate that an iron containing writing material was used to write on these tally sticks.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.084
GPT teacher head0.213
Teacher spread0.129 · 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 designQualitative
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
Published2018
Admission routes1
Has abstractyes

Explore more

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