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
We anticipate extensive applications of digital watermarking in the future electric power systems, which can be copyright protection, content authentication, quality measurement, database indexing and retrieval, etc. In this paper, we present a new digital image watermarking scheme that is invariant to rotation, scaling, and translation (RST). We embed watermark in the log-polar mappings (LPM) of the Fourier amplitude spectrum of an original image, so that image scaling results in a translational shift along the log-radius axis, that image rotation results in a cyclical shift along the angle axis, and that image translation has no effects in the LPM domain. In order to invert the translation effect in the LPM domain of image rotation and scaling, we propose our filtering method, which is new to our best knowledge. The new filtering method uses a small portion of the LPM spectrum of the original image to calculate the translated watermark positions. With minimum cost, the nearly-blind watermarking scheme avoids exhaustive search to save computation time and reduce false detection. The evaluations demonstrate that the performance of the scheme is very satisfactory.
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 | 0.003 |
| Open science | 0.001 | 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