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Record W2893823269 · doi:10.16995/dscn.283

4D Modelling of Built Heritage: A System Offering an Alternative to Using BIM

2018· article· en· W2893823269 on OpenAlex
Nathalie Charbonneau, Nicolas Spiric, Vanessa Blais, Léon Robichaud, Joanne C. Burgess

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDigital Studies / Le champ numérique · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topic3D Surveying and Cultural Heritage
Canadian institutionsUniversité de SherbrookeCegep Edouard MontpetitUniversité du Québec à Montréal
Fundersnot available
KeywordsPython (programming language)Cultural heritageComputer scienceClass (philosophy)HumanitiesArt historyArtHistoryProgramming languageArchaeologyArtificial intelligence

Abstract

fetched live from OpenAlex

<p class="p1">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. <p class="p1"> <p class="p1">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<span class="Apple-converted-space"> </span>pour tester le protocole développé parce qu’il est composé de plusieurs bâtiments ayant évolués de façon asynchrone.<span class="Apple-converted-space"> </span>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.696

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.115
GPT teacher head0.283
Teacher spread0.168 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it