Capturing Cosmic Ray Research and Researchers with Art
Bibliographic record
Abstract
We describe our experiment with an alternate approach to presenting cosmic ray research. The goal was to more widely promote cosmic ray research and attract diverse audiences, especially those from groups that are underrepresented in science or that do not have experience attending science outreach events. The IceCube Neutrino Observatory education and outreach team brought together local teenagers, internationally accomplished artists, science communicators, and scientists to produce an interactive gallery exhibit, Messages, that explores the cosmic ray community and science. The artists collaborated with the scientists and students to create two original installations that will be displayed at the UW--Madison Memorial Union Gallery for six weeks, from mid-June, 2019, through the end of the International Cosmic Ray Conference 2019. Event Horizon by Abdu'Allah with Ladoni features portraits of cosmic ray researchers and high school students who are learning more about the field. This installation will examine the science community as it is and as it could be. Messages from the Horizon by Hosale with Madsen is inspired by previous immersive works. It combines sound and light to explore what we know and how we know it.
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 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; 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".