Bibliographic record
Abstract
[Inicio] Ana Soler es única. No sólo porque desarrolle su arte de múltiples formas dejando siempre una huella reconocible. No sólo porque lo que hace traslade a la vez la necesidad de una reflexión y una emoción estética inmediata. No sólo porque parezca estar en posesión intrínseca de la materia misma y se exprese simultáneamente con vida, viveza y vitalidad. No sólo porque sea Premio Nacional de Grabado. No sólo porque pueda hablar del silencio, del dolor y hacernos oir voces, gritos y chirridos. No sólo porque sea capaz de cruzar un océano a nado con tres mil cuchillos para filete y una idea. No, no sólo por eso. Ana es única porque el arte así lo exige y ella así lo ha entendido. La instalación Puñaladas en el Aire que Ana montó para la Embajada de España en Canadá en la Galería SAW de Ottawa dejará una impronta imborrable en la memoria de todos los que la vieron. La violencia luminosa que resplandía sin agredir desde los filos de todos esos cuchillos era alternativamente cosquilleo embriagado y eso que Sloterdijk llamó algodicia, lo que quizá sea lo mismo. [...]
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.148 | 0.071 |
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 source (direct Gemma or distilled Codex), 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".