Parallel Development of Parametric Design Models Using Subjunctive Dependency Graphs
Why this work is in the frame
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Bibliographic record
Abstract
Exploring problems through multiple alternatives is a key aspect of design. In this paper, we present a prototype system as an extension to existing parametric CAD tools that enables parallel generation and editing of design alternatives. The system is built on two fundamental ideas. First, use of subjunctive dependency graphs enables simultaneous work on multiple design variations. These graphs capture and reveal complex data flow across alternative parametric CAD models. Second, prototype-based modeling provides a weak notion of inheritance enabling incremental description of differences between alternatives. The system is intended to be general enough to be used in different CAD platforms and other systems using graph-based modeling. The three basic system functions are definition of alternatives (variations) using prototype-based modeling, structural and parametric divergences of the prototypes, and interactive comparison. The goal of this research is consistent with the general qualities expected from any creativity support tools: enabling exploration and simultaneous development of variations.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it