The effects of ultraviolet and visible light on common furs: Color changes, photooxidation and the use of Tinuvin 292 as a photoprotectant
Bibliographic record
Abstract
Abstract In order to determine the light sensitivities of commonly encountered furs, 17 furs from 12 species were exposed to 1.97 Mlx hours of light from a xenon arc lamp, filtered either to simulate window-filtered daylight or to remove all ultraviolet (UV) radiation. Comparison with coexposed Blue Wools showed that most samples were relatively lightfast (Blue Wool 5 or better), with darker specimens being more lightfast. Examination of the Commission internationale de l'éclairage (CIE) L*a*b* values revealed fading but also other changes: some furs darkened, and other experienced changes in b* values. Removal of UV radiation prevented darkening and usually decreased the magnitude of ΔE76 but did not prevent color changes, and one species exhibited greater change under visible light. Changes in color were accompanied by photooxidation of the keratin of all species as assessed by attenuated total reflectance infrared spectroscopy; the extent of photooxidation was decreased by filtering out UV radiation. Pre-exposure treatment with a spray application of a 1% solution of Tinuvin 292, a hindered amine light stabilizer, offered some protection against both UV and visible light-induced changes. Tinuvin 292 pre-exposure also helped prevent keratin photooxidation and light-induced mechanical damage and thus may be an appropriate preventative treatment when light exposure is unavoidable.
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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 | 0.000 | 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) | 0.001 | 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".