A Comparative Analysis of the Complexities of Building Information Model(ling) Guides to Support Standardization
Bibliographic record
Abstract
The current approach to the development of a building information modelling (BIM) standard or guideline has provisioned for each individual authority in a unique way. There has been no universally standardized format, content or defined concepts employed in document development from one organization or region to the next. Though format and content vary widely according to the specific document scope and context, many published BIM guides around the world define the same, or similar, terms and concepts. The BIM guides project is the first attempt to leverage these existing publications within an open process of peer review and consensus standardization. It is believed that this structured approach to BIM document development will deliver increased efficiency in the creation and implementation of future Guidelines and Standards, contributing to the adoption and standardization of BIM within industry and providing the much needed universal baseline from which the many user-types of BIM can effectively build their knowledge, skills and abilities.
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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 | 0.132 | 0.279 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| 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".