Magical Fresh & Salty Conversation: Radio AmnionTBA21-Academy Radio
Bibliographic record
Abstract
In this episode, we are joined by Jol Thoms, a London-based artist and researcher teaching the MA program Art & Ecology at Goldsmiths, University of London. Thoms is the founder of a multi-year sound project called Radio Amnion, commissioning artists and researchers to stream sonic composition from the depths of the Pacific Ocean. Radio Amnion explores the magical spaces of intersection between cultural and scientific cosmologies and also joined the STARTS artists-in-residency for their final showcase event at Ocean Space in Venice on the summer solstice in 2021. In a conversation with Elisa Resconi, an astrophysicist from the Technical University of Munich, and Dwight Owens from Ocean Networks Canada, an initiative of ocean observatories monitoring the Canadian coastline, this episode delves into the deep world of ocean science and compassionate ecological art, departing from the smallest and perhaps most elusive particles described by physics. What happens when science opens up its depths to the transformative potential of art? "Magical Fresh & Salty Conversations is produced by TBA21–Academy with the support of STARTS, an initiative by the European Commission." Special thanks to our guests: Dwight Owens, Elisa Resconi, and Jol Thoms Editor at large: María Montero Sierra Sound edited by: Elena Zieser Introduction and credits voice-over: Nathan Johnson Music by horizonsnd and underwater sound recordings of the Venetian Lagoon by Sonia Levy and Jez Riley French Produced by: Miriam Calabrese, María Montero Sierra, Katarina Rakušček, and the artists.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.042 | 0.013 |
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".