Using retroReveal as a Complement to DStretch for Enhancing Red Ochre Pictographs
Bibliographic record
Abstract
The web-based program retroReveal has been used primarily for providing improved visibility of documents with faint text, including stamps, currency, music, and so forth. It has yet to be used to its full potential by archaeologists interested in rock art. The plugin DStretch, used on the ImageJ platform, has been the standard for enhancement of faint red ochre rock art images. We introduce retroReveal as a supplement to photographic investigation through comparison of images from four rock art sites in Alberta, Canada. Processing photographs with the two techniques typically yields comparable results, but often with slight differences. In a few cases, retroReveal makes certain features more apparent than is the case with DStretch; in other instances, the opposite is true. Other positive and negative aspects of the two techniques are discussed. Experiments with black pictographs indicate that retroReveal does not perform satisfactorily with these images. Overall, our results indicate that retroReveal should be added to the toolkit for illuminating painted rock art images.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".