SEED-Config: A case-based reasoning system for conceptual building design
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A case-based design functionality is a natural and intuitive addition to a design tool that can augment human capabilities and help designers remember and retrieve appropriate cases. SEED-Config, a design environment for conceptual building design, was developed to incorporate a case-based reasoning functionality to provide designers with initial potential solutions. The case representation in SEED-Config is the BENT information model, which records design knowledge, supports the hierarchical decomposition of design cases, offers multiple views, and encapsulates the outcome of the design in addition to the problem specification and the design solution. The case library was implemented in an object-oriented database management system to accumulate cases automatically and to provide efficient query facilities. The case retrieval aspect of SEED-Config offers three different methods to find the most useful cases stored in the case library: task-based, lineage-based, and customized. Case retrieval responds to the exploratory nature of the design process and supports versatile case retrieval by providing multiple paths to each case. The case adaptation aspect, which adjusts the selected case to the new problem to provide a complete solution, uses an adaptation method called derivational replay. The case-based design capabilities are completely integrated within the design environment from which the cases originate.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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