Programming in the model: A new perspective on scripting in CAD systems
Bibliographic record
Abstract
Scripting has become an integral part of design work in computer-aided design (CAD), especially with parametric systems.Designers who script face a steep learning and use curve due to the new (to them) script notation and the loss of direct manipulation of the model.Programming In the Model (PIM) is a prototype parametric CAD system with a live interface with side-by-side model and script windows; real-time updating of the script and the model; on-demand dependency, object and script representations in the model; and operation preview (lookahead).These features aim to break the steep learning and use curve of scripting into small steps and to bring programming and modeling tasks 'closer together.'A qualitative user study with domain experts and a focus group with HCI experts shows the importance of multi-directional live scripting and script localization within the model.Other PIM features show promise but require additional design work to create a better user experience.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.026 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".