Characterizing elegance of curves computationally for distinguishing Morrisseau paintings and the imitations
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
Computerized analysis of paintings has recently gained interest. The rapid technological advancements and the expanding interdisciplinary collaboration present us a promising prospect of computer-assisted authentication. We focus on the characterization of curve elegance. Specifically, we propose measures of curve steadiness and neighborhood coherence from brushstrokes. The technique has been applied to the paintings of renowned aboriginal Canadian artist Norval Morrisseau. Through computerized analysis of his authentic works and the imitations, it is revealed that the curves in his authentic paintings exhibit his commanding painting skills. The smooth and steady flow of the curves show less hesitancy of the artist than the authors of counterfeit works. The tangent angles tend to be more consistent along curves in the authentic paintings than in the imitations.
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 | 0.001 |
| 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