Bibliographic record
Abstract
dream.Medusa is a multimedia piece combining performance, responsive video, and audience feedback. Live vocalization and participant controlled devices provide interaction into a simulated lucid dream environment created with Max/MSP and Jitter. We discuss the concept of the piece, the interaction technologies, and the experience of performing with interactive participants. This document provides an overview of the concepts we would like to discuss in article-length format if our submission is accepted. 1. Concept The dream.Medusa performance was conceptualized as part of an installation exploring the stages of sleep and dreaming, created for the all night art festival Nuit Blanche in Toronto, Canada [1]. dream.Medusa uses live performance, video visualization and participant interaction to lead participants and observers through a simulated lucid dream. In a lucid dream, the dreamer becomes conscious that s/he can interact with and control events in the dream environment. In our performance, four participants holding specially created interactive objects become capable of interacting with the performing musician to create a visualization in a collaboratory fashion. The fifteen-minute piece begins with a singer guiding the development of the performance by using her voice to control a responsive video. As it progresses, the participants realize that they can effect change in the video visualizations by manipulating their abstractly designed controllers. The technology simulates the experience of lucid dreaming, in that the participants drift in and out of control of the dream-like experience. The result is an audio-visual performance that non-participatory audience members can observe in the manner of a traditional concert-style performance. The imagery and music is created with the goal of transporting both participatory and non-participatory observers into a dream-like, calm, and peaceful state, using videos of rhythmically moving jellyfish and a relaxing soundscape in order to encourage a restful and serene mood.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".