Bibliographic record
Abstract
Collective reality was an immersive environment delivered through multichannel video and audio, projection mapping and motion tracking, intended to be experienced by large groups in real-time. The work was commissioned by NESTA for their 2016 Futurefest event in London's Tobacco Dock in 2016. A second version of the work, reconfigured for a fulldome environment, was presented at Immersion Experience in the 4-storey Satosphere at Montréal’s Société des Artes Technologiques in 2017.<br><br>This Collection comprises a multi-component output with contextualising information, evidencing the two immersive experience events, Futurefest and Montréal’s Société des Artes Technologiques, in the form of: audio documentation of the Collective Reality installation, with all sound generated in real time in response to the movements of visitors to the installation; video documentation of the NESTA installation at Futurefest; photo documentation of a Collective Reality event at FutureFest 2016; and photo documentation of a Collective Reality event at IX SAT 2017. Contextualising evidence includes a 300-word statement, research timeline, research questions, and photo documentation of the 2016 residency and construction.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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; both teacher heads agree on what is shown here.
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".