Toward Responsive Atmospheres: Prototype Exploration through Material and Computational Systems
Bibliographic record
Abstract
The Stratus Project is an ongoing body of design research investigating the potential for kinetic, sensing and environment-responsive interior envelope systems. The research emerges from a consideration of our attunement to the soft systems of architecture – light, thermal gradients, air quality and noise – paired with a desire to develop and prototype envelopes that not only perform to affect these atmospheres, but also to promote continual information and material exchange, and eventually dialogue, between occupant and atmosphere. Stratus v1.0 included the construction of a modest prototype using simple open source technologies, aimed to explore the formal, operational and technological possibilities, as well as potential operability and control conflicts, as part of the first phase of thinking around these questions. It deploys a distributed approach to structural, mechanical and communications systems design and delivery, where localized response is prioritized. The project works to reclaim the environmentally performative elements of architecture – in this case, specifically, interior mechanical delivery and interface systems – to within the purview of the discipline, as territories of material, formal, technological and experiential innovation and exploration. This paper will describe both the development of the current prototype as well as future research and investigation trajectories. The Stratus Project begins by situating itself at the crossroads of the disciplinary territories of architecture, technology, environmental control and cybernetics. Through the use of computational technologies and in collaboration with researchers in the fields of computer science, mechanical engineering and materials science, this project aims to advance the development of responsive environmental design and performative building skins.
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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".