AMBIANTAL ARCHITECTURE − Defining the role of water in the aesthetic experience of sensitive architectural ambiances
Bibliographic record
Abstract
As part of an aesthetic approach, this design-driven research crosses two methodologies to determine what is common in the perception of atmospheres. First, a case study of the Vals’ thermal baths led to the selection of five different atmospheres, which were then analyzed through Gaston Bachelard’s lens, using his bookL’Eau et les rêves. Bachelard’s literary symbols echo in the water contained in the massive stone walls of Vals to identify common generators of sensitive atmospheres. Secondly, the construction of this dialogue between Bachelard and Zumthor leads to the elaboration of a conceptual architecture project which is voluntarily emotional. This project introduces the elements that generate five ambiences identified in the case study. This design-driven research is therefore based on Grégoire Chelkoff’s theory offormantsas vectors of transmission of atmosphere, pre-existing to the experienc of a place, of an ambiance, which itself is understood as a sensitive result of the perception of the space. The present work therefore questions the role of water as a sensitive vector, from the architecture to its visitor. The goal is to determine how water, in varying manifestations, can be used by architects to create a “mise en scène” for a voluntarily emotional architecture.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".