Bibliographic record
Abstract

 
 
 Access to water has been a subject in my work since I can remember. After hurricanes Irma and María it became more about aligning my artistic practice with a proposal that moves me. Since 2012 I have been studying natural clay deposits and since 2017 I have been doing so with the intention to clean water. This has been pretty much nonstop. For much of Puerto Rico and myself, water is natural abundance as well as a subject of disproportionate injustice; a subject of so much serenity yet also violence. When we immersed ourselves in nature during the conference, the lake was what pulled me. I was watching the waves: these being the physical manifestation of how wind and water negotiate by way of surface tension. As I was sitting there, following the reflections move, wanting to capture these ephemeral movements and colors travelling to depict the central idea of surface tension. I poured colors of the sunset, the trees, and various parts of the landscape on the canvas. It got messy really fast and appeared as though it would take forever to dry. In response to the rapidly approaching reconvening of the group, I placed a paper over the canvas to soak the runaway paint. While peeling the paper, I realized that I was feeling the resistance of the paint and the paper: instead of representing surface tension I began to experience the surface tension. This meant that there were now two paintings: one reflecting the other, both embodying surface tension rather than portraying it.
 
 
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.
How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".