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
As Guest editors, we have appreciated the opportunity to engage with a variety of authors working within the realm of Art and Artificial Intelligence (art+AI). The process of guest editing this special issue has expanded our consideration from three different professional stances. Campbell watches an art and design campus that hesitantly considers artificial intelligence as a possible contribution to artistic practice, while tracking a growing AI competence brewing with enthusiasm in a computer science department on a campus next door. Hedley considers artificial intelligence for its potential in facilitating 3-D geographic visualization, 3-D spatial interfaces, and 3-D data surveying as he considers AI methods to make progress on geographic challenges, while considering the art of designing of user interfaces intended to communicate knowledge. Hertzmann develops computer graphics and vision algorithms, and writes about how they interact with the worlds of art and perception.
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) | 0.000 | 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