4D Modelling of Built Heritage: A System Offering an Alternative to Using BIM
Bibliographic record
Abstract
The goal of our research is to improve the process of disseminating knowledge about built heritage. To this end, we propose to implement upgradeable digital models that include the time dimension. These models are designed to illustrate the evolution of heritage buildings and sites over time and record the historian’s interpretation of documentary sources. The research objective is to develop a 4D modelling protocol to optimize data organization so information is easier to access and modify. This paper explains why BIM platforms do not seem appropriate tools for the work we are doing. We describe our method based on the synergy between a SQLite database and a 3D software (Autodesk Maya) linked by an algorithm written in Python. We conducted a case study involving a heritage place in Montreal, Canada. This site provided an opportunity to test the protocol developed because it is composed of several buildings that have evolved asynchronously. L’objectif de notre recherche est de bonifier le processus de diffusion de la connaissance dans le domaine du patrimoine bâti. À cette fin, nous proposons la mise en oeuvre de modèles numériques évolutifs incluant la quatrième dimension, soit le temps. Ces modèles sont élaborés dans l’optique de rendre compte du processus évolutif de bâtiments et sites patrimoniaux, et de formaliser la façon dont l’historien interprète les sources documentaires. Nous avons développé un protocole de modélisation permettant d’optimiser l’organisation des données, afin d’en faciliter l’accès et la modification. Cet article explique pourquoi, dans le cadre de nos travaux, les plateformes BIM ne nous apparaissent pas comme étant des outils adéquats. Nous décrivons la méthode proposée, basée sur la synergie entre une base de données SQLite et un logiciel 3D (Autodesk Maya), liés entre eux par un algorithme écrit en Python. Nous avons réalisé une étude de cas portant sur un lieu patrimonial situé à Montréal, Canada. Ce site nous est apparu comme étant adéquat pour tester le protocole développé parce qu’il est composé de plusieurs bâtiments ayant évolués de façon asynchrone.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.008 |
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".