XPS and TOF‐SIMS applied to the study of ancient artifacts: Further studies on Alexandrian tetradrachms from the time of the Julio‐Claudian dynasty
Bibliographic record
Abstract
Two tetradrachms from the Diniacopoulos collection housed at Queen's University are the subject of this study. Previously, a protocol had been developed for a coin of the Emperor Claudius from the same collection, which showed that a combination of Time‐of‐Flight Secondary Ion Mass Spectrometry (TOF‐SIMS), Energy Dispersive X‐ray Spectroscopy (EDX), and X‐ray Photoelectron Spectroscopy (XPS) could provide information and identify areas of interest for additional analysis, thereby minimizing the amount of damage incurred. This is now applied to two more tetradrachms issued by the same mint and dated respectively to the time of Tiberius (14–37 AD) and Nero (54–68 AD). Preliminary results have indicated both differences and similarities between these coins and that from the time of Claudius. By comparing these results, it is hoped that information as to how the coins were made can be elucidated, shedding light on the different components and composition of the alloys produced in the same mint but at different time periods. Moreover, the detection and the identification of corrosion products, along with understanding what restorations methods may have been applied in the past, can guide conservators to determine what conservation treatment and preservation strategies are most appropriate for these antiquities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".