The VR Kiosk How observant passive VR storytelling enhanced the physical tour of parliament hill and disseminated the rehabilitation project
Bibliographic record
Abstract
2017 marks Canada's 150thbirthday which brought an estimated one million visitors to Ottawa - Canada's capital and to the parliament buildings. Carleton Immersive Media Studio (CIMS), in partnership with Public Services and Procurement Canada (PSPC), saw this as an opportunity to leverage digital assets already created by CIMS for the ongoing rehabilitation project of the parliament buildings. The result is the VR Kiosk: converted from an old shipping container with five walk up virtual reality (VR) stations that each contain five VR experiences to view. From May to September 2017, the VR Kiosk operated in front of the Capital Information Kiosk across the street from Parliament Hill in Ottawa, Canada. Each experience is designed to enhance the physical tour of Parliament Hill and help disseminate the upcoming rehabilitation project of the Centre Block of Parliament. CIMS developed the content of the VR experiences by creating 360 panoramas and utilizing the point clouds and building information model (BIM) completed for the preparation of the upcoming construction that will close the iconic building for a decade beginning in 2018. In order for the experiences to be accessible to a large demographic of visitors with varied technical skills, CIMS chose to create observant passive VR experiences in the form of 360 degree panoramic videos. The choice of an observant passive VR experience was made to meet the goals of accessibility, a pleasurable experience, and ease speed of operation. This paper will discuss what the VR Kiosk is, why the choice for an observant passive VR experience was made, and how the content was received.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.037 | 0.005 |
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".