Silver and Acid-thiourea Silver Dips: Rinsing and Aging Monitored by Electrochemistry
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.
Bibliographic record
Abstract
Many conservators are reluctant to use silver dips based on thiourea because of reported problems such as yellowing and retarnishing as well as brown spots on daguerreotypes. Silver dips are reported to leave a surface layer, which is blamed for these problems. Here, acid-thiourea silver dips (1 M thiourea, pH 2) were studied with samples of pure silver to see whether extensive rinsing can remove the surface layer, and what consequences the layer produces. It was shown that potentiodynamic scans can detect the presence of the surface layer. The electrochemical measurements were used to study the effects of rinsing (different times, different pH) and the effects of aging (28 days, 60°C, 100% relative humidity) on silver samples after immersion in a silver dip. The surface layer is partly modified, but not completely removed, even after 24 h of rinsing. The electrochemical signal of the surface layer is gone after aging. Moreover, dipped silver samples after rinsing do not tarnish more rapidly than samples of clean, polished silver. The problems reported with silver dip may be due to thiourea trapped in porosity rather than adsorbed on the surface.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it