Bibliographic record
Abstract
Beginning with the hypothesis that cultural heritage embodies both tangible and intangible values in its definition; this thesis proposes that if we are to truly experience heritage through virtual means, both sets of values must be incorporated into the experience.The project presented in this paper exists in the intersection of three fields of study: cultural heritage, virtual reality, and video games.Virtual reality technology has allowed us the opportunity to accurately visualize the physical characteristics of a space around us, with the emphasis residing primarily on the visual and sensory experience.Immersive video games place emphasis on a user's cognitive or emotional experience in virtual space by creating relationships and building value systems within the game worlds.Through the sensory stimuli of the former, and the cognitive and emotional stimuli of the latter, a combined methodology is proposed to create a fully immersive virtual environment that allows a user the opportunity to experience the intangible emotional and cognitive values of architectural heritage in addition to the already well-established tangible spatial experiences achieved by virtual reality.This thesis begins with establishing a definition of cultural heritage and a critical analysis of existing technologies and methodologies used in its representation through virtual heritage.It is then followed by a discussion of the video game industry, and how it addresses the elements lacking in the previous analysis, with emphasis on intangible cognitive experiences.Finally, a characteristic framework that merges the successes of both industry methodologies is proposed to demonstrate the possibilities of experiencing iii the intangible values of heritage, using the Carbide Willson Mill ruins site in Gatineau Park as a project example.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".