Implicit Fabrication, Fabrication Beyond Craft: The Potential of Turing Completeness in Construction"
Bibliographic record
Abstract
This paper addresses the limited shared vocabulary of landscape architecture and architectural design, evident in the application of terms such as “spatial design” and “spatial planning.” In their current usage, such terms emphasize the visible, terrestrial, pedestrian-perspective level, often to the absolute exclusion of a spatial, i.e., volumetric comprehension of the environment. This deficit is acutely evident in the teaching of landscape architecture and architecture and discussion of these fields’ shared ground. The dominant document type for mapping such analysis and design is the plan, or three-dimensional representations of the same, restricted to an extrusion or height map. GIS techniques in spatial design tend to be weighted toward visual, surface-based data (slope analysis, exposure, viewshed, etc.). Within this domain, our goal is to transform aspects of the intangible—the characteristics of open space itself—into a form that is legible, quantifiable, and malleable.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.032 |
| Scholarly communication | 0.006 | 0.019 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".