Book of Abstracts of ESPACIAR 2025: Digitalstage. Spatial Analysis of Digital Stage Installations of the 21st Century
Bibliographic record
Abstract
Se propone este encuentro académico y artístico para profundizar, desde lo arquitectónico, en el estudio de la nueva espacialidad que viene generándose, desde los 80, y especialmente durante el s.XXI, en las instalaciones escenográficas digitales (artísticas, culturales, escénicas o audiovisuales), debido a la incorporación disruptiva del software: videomapping, stagebots, ambiente sonoro, realidad aumentada, modelado y proyección 3D, visión 360º, hologramas… Esta innovadora gestión multimedia ha propiciado posibilidades de expresión y configuraciones plásticas antes impensables.La escena se hace tan ilusionista e inmersiva como en el teatro a la italiana, a la vez que, paradójicamente, es más interactiva.La arquitectura como arte del espacio puede extraer precisas enseñanzas de las instalaciones, que son experimentaciones más ágiles, porque están menos sometidas a la normativa y la razón de uso propias de lo edificado.Parece oportuno abordar este trasvase de procedimientos mediante aproximaciones interdisciplinares de integración, interacción, interpretación o experiencia.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.284 | 0.066 |
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".