HBIM ORIENTED TOWARDS THE MASTER PLAN OF THE CHARTERHOUSE OF JEREZ (CÁDIZ, SPAIN)
Bibliographic record
Abstract
Abstract. This paper is focused on the possibilities of Heritage Building Information Modelling HBIM to enhance the strategic planning of large monuments ensembles in a Master Plan. The study case is the Charterhouse of Jerez (Cádiz, Spain), a monument acknowledged with the highest level of legal protection since 1856. Its HBIM model, developed with a Level of Knowledge LOK200, provides appropriate alphanumerical and graphical outputs for strategic decision-making on the major guidelines of heritage management: research, protection, conservation and dissemination. This LOK200 HBIM model emerges from the integration of graphic information produced with different techniques, from historic plans to photogrammetric surveys. In relation to research, the architectural analysis required to generate the HBIM model has defined its constructive elements and spaces, its construction process and the higher heritage potential areas. In addition, the synthetic views produced from the model have allowed unexpected relationships and conclusions about the monument. In relation to protection, a precise delimitation of the monument site and its surroundings have been defined. Furthermore, areas with different levels of vulnerability have been characterized. In relation to conservation, the severity of the damages in the main structures and the urgency of the interventions have been defined. In relation to dissemination, the relationship between its current religious use and the odds for public visit have been presented.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".