Bibliographic record
Abstract
Instruments of Gaia is a thesis which interviews the role of architecture as an interface between nature and human experience. The contained argument is a critique on architecture’s reliance on climatic mitigation; whereas relationships between site and user are nullified through concealed building systems. This thesis project as a counterpoint explores new ideas of architectural design and expression as a register for and active agent in the anthropocene where the magnification and understanding of place and site plays a key role in the development of the climatic imagination needed ever more, to grapple with human impact on the very ground we rest our foundations upon. Architectural expression as an intuitive, didactic mechanism and amplifier of this relationship is explored through the collapsing of multidisciplinary research, and expression of the fragility, and enormity of Gaia as a new secular mythos of the cosmos, and the embedding of these new myths, through weathering and geologic time scales, into an architectural project. The experiential memories formed within this expanded field of architecture constitute a new body of sensible knowledge. The art of architecture offers the medium with which to collapse these assemblages into poetic space and memory, and the beginning of a new dialogue with the Gaia of the Anthropocene.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.036 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".