Querying IFC-Based Building Information Models to Support Construction Management Functions
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
The design and construction community has shown increasing interest in adopting Building Information Models (BIM). While the richness of design information offered by BIM is evident, there are still tremendous challenges in getting construction-specific information out of BIM, particularly from IFC-based product models. This paper describes our approach for querying construction-specific design conditions from an IFC-based model. The approach involves: (1) the formalization of construction-specific design conditions as an ontology of product features, (2) the automated generation of feature-based product models for a particular construction domain and function, and (3) a formal specification that supports user-driven queries of the feature-based model. This approach allows practitioners to answer a broad range of user-customizable queries in support of different construction management functions. It also transforms designer-focused EFC-based models into construction-focused, feature-based models.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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