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
Whether in visual expressions or in texts, erasures are invitations to scrutinize, read, and interpret. Marking a mutation in style, content or form, they are about presence and absence, mutations and updates, old and new versions, a “before” and an “after.” An erasure may be an action (that of deleting), a state (the blankness resulting from this action) or the juxtaposition of what has been erased, still visible, and of the new mark or script replacing it (also named “sous-rature,” often translated as “under erasure."
 This exhibition welcomes different types of erasures, be they scenes lacking important elements, simplified adaptations of existing artworks, or abstracted forms of figurative objects. 
 To accompany these pieces, short written statements commenting on well-known digital artworks result from extensive editing as well as our readiness to create voids and unusual associations. 
 Rather than correcting something wrong, erasures are signs of process and of an expanding imagination.
 Curators: Shawn Serfas and Catherine Parayre
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) | 0.030 | 0.006 |
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